{"Video ID": "Jk1YP4Y_U_0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Stoic Philosophy Text Generation with TensorFlow", "Time Created": "2020-04-19 11:33:45 UTC", "Time Published": "2020-04-19 13:52:43 UTC", "Duration": "1859 seconds", "Description": "Explanation of key parts to a RNN text generator built in TensorFlow with Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nI've written a couple of Medium articles on this project, if you're interested check them out here:\nStoic Philosophy - Built by Algorithms\nhttps://towardsdatascience.com/stoic-philosophy-built-by-algorithms-9cff7b91dcbd\nSupercharged Prediction with Ensemble Learning\nhttps://towardsdatascience.com/recurrent-ensemble-learning-caffdcd94092\n\nMusic used by Lakey Inspired.\n1 - Blue Boi\n2 - Falling\nhttps://www.youtube.com/channel/UCOmy8wuTpC95lefU5d1dt2Q", "Category": "People & Blogs", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "gXqHd6-NKBo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build TensorFlow Pipelines with tf.data.Dataset", "Time Created": "2020-11-02 08:23:38 UTC", "Time Published": "2020-11-02 08:57:48 UTC", "Duration": "1853 seconds", "Description": "Link to updated version (without video freeze): https://youtu.be/f6XVfgJTbp4\n\nAn introduction to building better input pipelines for Machine Learning in TF2.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to tf.data API docs: https://www.tensorflow.org/guide/data", "Category": "People & Blogs", "Like Count": 46.0, "Dislike Count": 9.0}
{"Video ID": "yYEPNla4tlQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Every New Feature in Python 3.10.0a2", "Time Created": "2020-11-08 18:09:49 UTC", "Time Published": "2020-11-10 16:44:05 UTC", "Duration": "883 seconds", "Description": "Every new feature in the early release alpha 2 preview of Python 3.10\n\nThere is video lag 5:00 - 9:55 covering the Type Alias section (sorry!) - the audio is okay though\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "People & Blogs", "Like Count": 88.0, "Dislike Count": 5.0}
{"Video ID": "GYDFBfx8Ts8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Build a Transformer for Language Classification in TensorFlow", "Time Created": "2020-11-19 09:57:27 UTC", "Time Published": "2020-11-19 12:20:35 UTC", "Duration": "2299 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHow to build a transformer model for sentiment analysis (language classification) using HuggingFace's Transformers library in TensorFlow 2 with Python.\n\nWe cover the full process from downloading data all the way through to building and training the transformer model.\n\nThis is a multi-class classification problem using both TensorFlow and Transformers to build a multiclass sentiment classifier.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nArticle version is here:\nhttps://betterprogramming.pub/build-a-natural-language-classifier-with-bert-and-tensorflow-4770d4442d41\n\nOr here (free link if you don't have Medium membership):\nhttps://betterprogramming.pub/build-a-natural-language-classifier-with-bert-and-tensorflow-4770d4442d41?sk=346cd4ce5ee019c400835588b56d8574\n\nArticle extract:\n\"High-performance transformer models like BERT and GPT-3 are transforming a huge array of previously menial, language-based tasks, into the work of a few clicks, saving a lot of time.\n\nIn most industries, the newest wave of language optimization is just getting started \u2014 taking their first baby steps. But these seedlings are widespread, and sprouting quickly.\n\nMuch of this adoption is thanks to the incredibly low barrier-to-entry. If you know the basics of TensorFlow or PyTorch, and take a little time to get to grips with the Transformers library \u2014 you\u2019re already halfway there.\n\nWith the Transformers library, it takes just three lines of code to initialize a cutting-edge ML model \u2014 a model built from the billions of research dollars spent by the likes of Google, Facebook, and OpenAI.\n\nThis article will take you through the steps to build a classification model that leverages the power of transformers, using Google\u2019s BERT.\n\nTransformers\n- Finding Models\n- Initializing\n- Bert Inputs and Outputs\nClassification\n- The Data\n- Tokenization\n- Data Prep\n- Train-Validation Split\n- Model Definition\n- Train\"", "Category": "People & Blogs", "Like Count": 384.0, "Dislike Count": 12.0}
{"Video ID": "DgGFhQmfxHo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to use the Kaggle API in Python", "Time Created": "2020-11-22 20:19:30 UTC", "Time Published": "2020-11-22 20:29:27 UTC", "Duration": "462 seconds", "Description": "Simple step-by-step tutorial covering the setup and use of the Kaggle API for downloading datasets using the Kaggle library in Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "People & Blogs", "Like Count": 121.0, "Dislike Count": 6.0}
{"Video ID": "YvVQgvAz9dY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Language Generation with OpenAI's GPT-2 in Python", "Time Created": "2020-11-23 12:36:44 UTC", "Time Published": "2020-11-24 14:22:46 UTC", "Duration": "498 seconds", "Description": "Easy natural language generation with Transformers and PyTorch. We apply OpenAI's GPT-2 model to generate text in just a few lines of Python code.\n\nLanguage generation is one of those natural language tasks that can really produce an incredible feeling of awe at how far the fields of machine learning and artificial intelligence have come.\n\nGPT-1, 2, and 3 are OpenAI\u2019s top language models \u2014 well known for their ability to produce incredibly natural, coherent, and genuinely interesting language.\n\nIn this article, we will take a small snippet of text and learn how to feed that into a pre-trained GPT-2 model using PyTorch and Transformers to produce high-quality language generation in just eight lines of code. We cover:\n\nPyTorch and Transformers\n- Data\nBuilding the Model\n- Initialization\n- Tokenization\n- Generation\n- Decoding\nResults\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium Article:\nhttps://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b\n\nFriend Link (free access):\nhttps://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b?sk=930367d835f15abb4ef3164f7791e1b1\n\nThumbnail background by gustavo centurion on Unsplash\nhttps://unsplash.com/photos/O6fs4ablxw8", "Category": "People & Blogs", "Like Count": 133.0, "Dislike Count": 1.0}
{"Video ID": "egDIqQIjDCI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Text Summarization with Google AI's T5 in Python", "Time Created": "2020-11-24 21:26:27 UTC", "Time Published": "2020-11-27 06:00:07 UTC", "Duration": "419 seconds", "Description": "Easy text summarization using Google AI's T5 model using HuggingFace transformers and PyTorch in Python.\n\nAutomatic text summarization allows us to shorten long pieces of text into easy-to-read, short snippets that still convey the most important and relevant information of the original text.\n\nIn this video, we\u2019ll build a simple but incredibly powerful text summarizer using Google\u2019s T5. We\u2019ll be using the PyTorch and HuggingFace\u2019s Transformers frameworks.\n\nThis is split into three parts:\n1. Import and Initialization\n2. Data and Tokenization\n3. Summary Generation\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nYou can read the article version of this on Medium here:\nhttps://betterprogramming.pub/how-to-summarize-text-with-googles-t5-4dd1ae6238b6\n\n(And for those of you without Medium membership, here's a free link):\nhttps://betterprogramming.pub/how-to-summarize-text-with-googles-t5-4dd1ae6238b6?sk=740d3009282cb2c4f7478a0c073dedb3\n\nThumbnail background by gustavo centurion on Unsplash\nhttps://unsplash.com/photos/O6fs4ablxw8", "Category": "People & Blogs", "Like Count": 115.0, "Dislike Count": 1.0}
{"Video ID": "DFtP1THE8fE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to do Sentiment Analysis with Flair in Python", "Time Created": "2020-12-04 11:15:10 UTC", "Time Published": "2020-12-04 14:00:03 UTC", "Duration": "848 seconds", "Description": "Learn how to perform powerful sentiment analysis with no fine-tuning or pre-training required using the Flair NLP library in Python.\n\nWith the real-time information available to us on massive social media platforms like Twitter, we have all the data we could ever need to create these accurate and up-to-date sentiment metrics for different companies.\n\nBut then comes the question, how can our computer understand what this unstructured text data means?\n\nThat is where sentiment analysis comes in. Sentiment analysis is a particularly interesting branch of Natural Language Processing (NLP), which is used to rate the language used in a body of text.\n\nThrough sentiment analysis, we can take thousands of tweets about a company and judge whether they are generally positive or negative (the sentiment) in real-time!\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/sentiment-analysis-for-stock-price-prediction-in-python-bed40c65d178\n\n(Free link if you don't have Medium membership):\nhttps://towardsdatascience.com/sentiment-analysis-for-stock-price-prediction-in-python-bed40c65d178?sk=1cbf33a5d1fd2ed841f9487972c1cbed\n\nThumbnail photo by Alexander London on Unsplash\nhttps://unsplash.com/@alxndr_london", "Category": "People & Blogs", "Like Count": 64.0, "Dislike Count": 2.0}
{"Video ID": "8o3jvkK2GGU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Python Environment Setup for Machine Learning", "Time Created": "2020-12-23 13:50:07 UTC", "Time Published": "2020-12-23 13:53:02 UTC", "Duration": "754 seconds", "Description": "Everything you need for a Python environment set up for Machine Learning and Data Science!\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/how-to-setup-python-for-machine-learning-173cb25f0206\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Christian Wiediger on Unsplash\nhttps://unsplash.com/@christianw", "Category": "People & Blogs", "Like Count": 38.0, "Dislike Count": 1.0}
{"Video ID": "BYbJ_HH788U", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Functional API - TensorFlow Essentials #2", "Time Created": "2020-12-28 16:41:11 UTC", "Time Published": "2020-12-29 10:04:40 UTC", "Duration": "341 seconds", "Description": "A look at the functional API method for building models in TensorFlow 2 for Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Darius Bashar on Unsplash\nhttps://unsplash.com/@dariusbashar?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "_8Bydxud1XU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training Parameters - TensorFlow Essentials #3", "Time Created": "2020-12-28 19:30:23 UTC", "Time Published": "2020-12-29 23:37:57 UTC", "Duration": "450 seconds", "Description": "Learn how to set up model training parameters and compile the model before training.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Alex McCarthy on Unsplash\nhttps://unsplash.com/@4lexmccarthy?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 17.0, "Dislike Count": 0.0}
{"Video ID": "f6XVfgJTbp4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Input Data Pipelines - TensorFlow Essentials #4", "Time Created": "2020-12-28 23:25:54 UTC", "Time Published": "2020-12-30 11:30:02 UTC", "Duration": "751 seconds", "Description": "Learn how to set-up efficient and clean input data pipelines using tf.data.Dataset\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Daria Nepriakhina on Unsplash\nhttps://unsplash.com/@epicantus?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 54.0, "Dislike Count": 0.0}
{"Video ID": "MQD1yMnZ_jk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sequential Model - TensorFlow Essentials #1", "Time Created": "2020-12-29 09:46:00 UTC", "Time Published": "2020-12-29 09:50:23 UTC", "Duration": "391 seconds", "Description": "Learn how to use the sequential model building approach in TensorFlow 2.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nBackground thumbnail by Aryan Dhiman on Unsplash\nhttps://unsplash.com/@mylifeasaryan_?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 84.0, "Dislike Count": 1.0}
{"Video ID": "KTFWNI0qL28", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "6 of Python's Newest and Best Features (3.7-3.9)", "Time Created": "2021-01-12 23:31:26 UTC", "Time Published": "2021-01-12 23:58:12 UTC", "Duration": "1084 seconds", "Description": "A rundown of the six most recent, and coolest features added to Python in the past few years!\n\n2018 brought us a plethora of new features with the release of Python 3.7, followed by 3.8 in 2019, and 3.9 in 2020.\n\nMany of those changes were behind the scenes. Optimizations and upgrades that the vast majority of us will never notice, despite their benefits.\n\nOthers are more obvious, additions to syntax or functionality that can change how we write our code. But even these visible changes can be hard to keep up with.\n\nIn this video, we will run through the more apparent upgrades to provide a brief but hopefully invaluable refresher on everything new to Python from the past few years.\n\n- Python 3.7\n  - Breakpoints\n- Python 3.8\n  - Walrus Operator\n  - F-string '=' Specifier\n  - Positional-only Parameters\n- Python 3.9\n  - More Type Hinting\n  - Dictionary Unions\n\nMedium Article:\nhttps://towardsdatascience.com/amazing-features-added-to-python-from-3-7-to-now-4f35f0bb1ea6\n\n(Free access link):\nhttps://towardsdatascience.com/amazing-features-added-to-python-from-3-7-to-now-4f35f0bb1ea6?sk=bda3cb7717caa969b81619f85191f241\n\nThumbnail background by Martin Sanchez on Unsplash:\nhttps://unsplash.com/photos/4PDPLw1flgE\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 15.0, "Dislike Count": 2.0}
{"Video ID": "GyJtxd14DTc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Novice to Advanced RegEx in Less-than 30 Minutes + Python", "Time Created": "2021-01-27 09:06:42 UTC", "Time Published": "2021-01-27 09:51:32 UTC", "Duration": "1769 seconds", "Description": "A full tutorial covering everything you need to know about Regular Expressions - an essential for anyone learning to code - and even more so for anyone interested in Natural Language Processing.\n\nThis video includes:\n\n- metacharacters\n- quantifiers\n- capture groups\n- using capture groups in Python\n- character sets\n- look-ahead and look-behind assertions\n- negative look-ahead and look-behind assertions\n- inline modifiers\n- passing modifiers as function parameters in Python\n- conditionals (if-else statements for RegEx)\n- re.match\n- re.search\n- re.findall\n\nWe cover all of this in-depth in this tutorial, incl. examples all the way through on RegEx101 (an interactive debugging/regex building tool) and also in Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 239.0, "Dislike Count": 8.0}
{"Video ID": "1ZcXmjZtJJ8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building a PlotLy $GME Chart in Python", "Time Created": "2021-02-02 13:38:16 UTC", "Time Published": "2021-02-07 13:24:45 UTC", "Duration": "4492 seconds", "Description": "A code-along video covering the coding process from imagination to Python.\nSomething a little different, I'm not overly keen on this format - it's pretty long - but I've recorded it and I think maybe this can be useful for a few of you.\nI haven't prepared anything beforehand, this is just going into the coding process with a rough outline of wanting to build a stock chart for GME (GameStop) and adding a few technical indicators - to get more familiar with PlotLy and the AlphaVantage API.\nSo, it's a weird one, but I hope a few of you enjoy it - thanks :)\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "ZIRmXkHp0-c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Custom Q&A Transformer Models in Python", "Time Created": "2021-02-09 20:42:56 UTC", "Time Published": "2021-02-12 13:30:03 UTC", "Duration": "4216 seconds", "Description": "In this video, we will learn how to take a pre-trained transformer model and train it for question-and-answering. We will be using the HuggingFace transformers library with the PyTorch implementation of models in Python.\n\nTransformers are one of the biggest developments in Natural Language Processing (NLP) and learning how to use them properly is basically a data science superpower - they're genuinely amazing I promise!\n\nI hope you enjoy the video :)\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/the-ultimate-performance-metric-in-nlp-111df6c64460\n\n(Free link):\nhttps://towardsdatascience.com/how-to-fine-tune-a-q-a-transformer-86f91ec92997?sk=9344fd51afe71a0905db833d0183d436\n\nCode:\nhttps://gist.github.com/jamescalam/55daf50c8da9eb3a7c18de058bc139a3\n\nPhoto in thumbnail by Lorenzo Herrera on Unsplash\nhttps://unsplash.com/@lorenzoherrera", "Category": "Education", "Like Count": 163.0, "Dislike Count": 5.0}
{"Video ID": "FdjVoOf9HN4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Use The Reddit API in Python", "Time Created": "2021-02-12 11:36:48 UTC", "Time Published": "2021-02-12 12:02:48 UTC", "Duration": "1401 seconds", "Description": "Learn how to use the Reddit API in Python, including setup, authorization, and pulling data from subreddits.\n\nReddit API docs:\nhttps://www.reddit.com/dev/api/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-use-the-reddit-api-in-python-5e05ddfd1e5c\n\n\ud83d\udcd6 Free link:\nhttps://towardsdatascience.com/how-to-use-the-reddit-api-in-python-5e05ddfd1e5c?sk=0295f297c1365bee7cc7a32bdff21b61\n\nExtract from article:\n\n\"Reddit is a huge ecosystem brimming with data that is readily available at our very fingertips. As a data-minded person, I wanted to take advantage of this and perform some analysis using this vast repository of open-source data.\nInitially, it turned out that getting to grip with Reddit\u2019s API wasn\u2019t as clear-cut as expected \u2014 despite being a straightforward process; it can be a little confusing at first.\nSo, after figuring everything out, I wrote this article \u2014 which I hope will help a few of you to get familiar with using the Reddit API in Python. We will cover:\nGetting Access\nMaking Requests\n  - Reading the Data\n  - Streaming New Posts\nParameters\n\nGetting Access\nFirst, we need access. Unlike most popular services, the Reddit API was somewhat difficult to figure out initially. There are several steps:\n1. Go to App Preferences and click create another app\u2026 at the bottom.\n2. Fill out the required details, make sure to select script \u2014 and click create app.\n3. make a note of the personal use script and secret tokens.\n4. Request a temporary OAuth token from Reddit. We need our username and password for this.\n5. Add headers=headers to every request. The OAuth token will expire after ~2 hours, and a new one will need to be requested.\n\"\n\nAnd so on, check it out if you're interested in reading (rather than watching).\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 627.0, "Dislike Count": 11.0}
{"Video ID": "scJsty_DR3o", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Q&A Models in Python (Transformers)", "Time Created": "2021-02-17 21:03:29 UTC", "Time Published": "2021-02-19 15:00:21 UTC", "Duration": "1189 seconds", "Description": "In this video we'll cover how to build a question-answering model in Python using HuggingFace's Transformers.\n\nYou will need to install the transformers library with:\npip install transformers\n\nAlongside either TensorFlow or PyTorch (to follow this video exactly you will need PyTorch). To install TensorFlow just type:\npip install tensorflow\nOR\nconda install tensorflow\n\nAnd for PyTorch follow the instructions under 'Install PyTorch' here:\nhttps://pytorch.org/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to Q&A fine-tuning video:\nhttps://youtu.be/ZIRmXkHp0-c\n\nYou can find the Medium article link below here:\nhttps://towardsdatascience.com/question-and-answering-with-bert-6ef89a78dac", "Category": "Education", "Like Count": 151.0, "Dislike Count": 1.0}
{"Video ID": "QJq9RTp_OVE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Decode Outputs From NLP Models (Python)", "Time Created": "2021-02-21 18:02:42 UTC", "Time Published": "2021-02-24 15:00:10 UTC", "Duration": "577 seconds", "Description": "In this video, we will cover three ways to decode the output probabilities from NLP models - greedy search, random sampling, and beam search.\n\nLearning how to decode outputs can make a huge difference in diagnosing model issues and improving text output quality - and as an added bonus it's super easy.\n\nOne of the often-overlooked parts of sequence generation in natural language processing (NLP) is how we select our output tokens \u2014 otherwise known as decoding.\n\nYou may be thinking \u2014 we select a token/word/character based on the probability of each token assigned by our model.\n\nThis is half-true \u2014 in language-based tasks, we typically build a model which outputs a set of probabilities to an array where each value in that array represents the probability of a specific word/token.\n\nAt this point, it might seem logical to select the token with the highest probability? Well, not really \u2014 this can create some unforeseen consequences \u2014 as we will see soon.\n\nWhen we are selecting a token in machine-generated text, we have a few alternative methods for performing this decode \u2014 and options for modifying the exact behavior too.\n\nIn this video we will explore three different methods for selecting our output token, these are:\n\n- Greedy Decoding\n- Random Sampling\n- Beam Search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to the article version on Medium:\nhttps://towardsdatascience.com/the-three-decoding-methods-for-nlp-23ca59cb1e9d\n\nFree link (if you don't have membership):\nhttps://towardsdatascience.com/the-three-decoding-methods-for-nlp-23ca59cb1e9d?sk=64fbb0204c174dc520af027a69f88030", "Category": "Education", "Like Count": 28.0, "Dislike Count": 0.0}
{"Video ID": "TCZgXFPNnbc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Identify Stocks on Reddit with SpaCy (NER in Python)", "Time Created": "2021-03-01 21:47:29 UTC", "Time Published": "2021-03-03 14:27:48 UTC", "Duration": "1307 seconds", "Description": "We will learn how to process unstructured text data from Reddit and extract organization names so that any further analysis is automatically classified and results assigned to the correct stocks.\n\nOrganizations are mentioned in each subreddit in a variety of formats. Typically we will find two formats:\n\n- Organization name, eg Tesla/Tesla Motors\n- Ticker symbol, eg TSLA, tsla, or $TSLA\n\nWe also need to be able to differentiate between tickers and other abbreviations/slang -some of these are unclear like AI (AI can mean both artificial intelligence and refer to the ticker symbol for C3.ai).\n\nSo, we need a reasonable competent NER process to accurately classify our data.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nReddit API video: https://youtu.be/FdjVoOf9HN4\n/r/investing data: https://github.com/jamescalam/transformers/blob/main/course/named_entity_recognition/data/reddit_investing.csv\nMedium article: https://towardsdatascience.com/ner-for-extracting-stock-mentions-on-reddit-aa604e577be\n(Free version if you don't have Medium membership): https://towardsdatascience.com/ner-for-extracting-stock-mentions-on-reddit-aa604e577be?sk=d16305d40b18e7955a0665633182d2b4\n\nThanks for watching!", "Category": "Education", "Like Count": 33.0, "Dislike Count": 0.0}
{"Video ID": "yDGo9z_RlnE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentiment Analysis on ANY Length of Text With Transformers (Python)", "Time Created": "2021-03-10 08:15:21 UTC", "Time Published": "2021-03-10 13:15:03 UTC", "Duration": "1630 seconds", "Description": "The de-facto standard in many natural language processing (NLP) tasks nowadays is to use a transformer. Text generation? Transformer. Question-and-answering? Transformer. Language classification? Transformer!\n\nHowever, one of the problems with many of these models (a problem that is not just restricted to transformer models)  is that we cannot process long pieces of text.\n\nAlmost every article I write on Medium contains 1000+ words, which, when tokenized for a transformer model like BERT, will produce 1000+ tokens. BERT (and many other transformer models) will consume 512 tokens max\u200a-\u200atruncating anything beyond this length.\n\nAlthough I think you may struggle to find value in processing my Medium articles, the same applies to many useful data sources\u200a-\u200alike news articles or Reddit posts.\n\nWe will take a look at how we can work around this limitation. In this article, we will find the sentiment for long posts from the /r/investing subreddit. This video will cover:\n\nHigh-Level Approach\nGetting Started\n- Data\n- Initialization\nTokenization\nPreparing The Chunks\n- Split\n- CLS and SEP\n- Padding\n- Reshaping For BERT\nMaking Predictions\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nHere's a link to the Medium article:\nhttps://towardsdatascience.com/how-to-apply-transformers-to-any-length-of-text-a5601410af7f\n\nAnd a free access link if you don't have Medium membership:\nhttps://towardsdatascience.com/how-to-apply-transformers-to-any-length-of-text-a5601410af7f?sk=d4e717eb2ff31fb27ea67019bbb63ad6", "Category": "Education", "Like Count": 111.0, "Dislike Count": 2.0}
{"Video ID": "9Od9-DV9kd8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Unicode Normalization for NLP in Python", "Time Created": "2021-03-16 09:27:24 UTC", "Time Published": "2021-03-17 13:30:00 UTC", "Duration": "927 seconds", "Description": "\u2115\ud835\udd60-\ud835\udd60\ud835\udd5f\ud835\udd56 \ud835\udd5a\ud835\udd5f \ud835\udd65\ud835\udd59\ud835\udd56\ud835\udd5a\ud835\udd63 \ud835\udd63\ud835\udd5a\ud835\udd58\ud835\udd59\ud835\udd65 \ud835\udd5e\ud835\udd5a\ud835\udd5f\ud835\udd55 \ud835\udd68\ud835\udd60\ud835\udd66\ud835\udd5d\ud835\udd55 \ud835\udd56\ud835\udd67\ud835\udd56\ud835\udd63 \ud835\udd66\ud835\udd64\ud835\udd56 \ud835\udd65\ud835\udd59\ud835\udd56\ud835\udd64\ud835\udd56 \ud835\udd52\ud835\udd5f\ud835\udd5f\ud835\udd60\ud835\udd6a\ud835\udd5a\ud835\udd5f\ud835\udd58 \ud835\udd57\ud835\udd60\ud835\udd5f\ud835\udd65 \ud835\udd67\ud835\udd52\ud835\udd63\ud835\udd5a\ud835\udd52\ud835\udd5f\ud835\udd65\ud835\udd64. \ud835\udd4b\ud835\udd59\ud835\udd56 \ud835\udd68\ud835\udd60\ud835\udd63\ud835\udd64\ud835\udd65 \ud835\udd65\ud835\udd59\ud835\udd5a\ud835\udd5f\ud835\udd58, \ud835\udd5a\ud835\udd64 \ud835\udd5a\ud835\udd57 \ud835\udd6a\ud835\udd60\ud835\udd66 \ud835\udd55\ud835\udd60 \ud835\udd52\ud835\udd5f\ud835\udd6a \ud835\udd57\ud835\udd60\ud835\udd63\ud835\udd5e \ud835\udd60\ud835\udd57 \u2115\ud835\udd43\u2119 \ud835\udd52\ud835\udd5f\ud835\udd55 \ud835\udd6a\ud835\udd60\ud835\udd66 \ud835\udd59\ud835\udd52\ud835\udd67\ud835\udd56 \ud835\udd54\ud835\udd59\ud835\udd52\ud835\udd63\ud835\udd52\ud835\udd54\ud835\udd65\ud835\udd56\ud835\udd63\ud835\udd64 \ud835\udd5d\ud835\udd5a\ud835\udd5c\ud835\udd56 \ud835\udd65\ud835\udd59\ud835\udd5a\ud835\udd64 \ud835\udd5a\ud835\udd5f \ud835\udd6a\ud835\udd60\ud835\udd66\ud835\udd63 \ud835\udd5a\ud835\udd5f\ud835\udd61\ud835\udd66\ud835\udd65, \ud835\udd6a\ud835\udd60\ud835\udd66\ud835\udd63 \ud835\udd65\ud835\udd56\ud835\udd69\ud835\udd65 \ud835\udd53\ud835\udd56\ud835\udd54\ud835\udd60\ud835\udd5e\ud835\udd56\ud835\udd64 \ud835\udd54\ud835\udd60\ud835\udd5e\ud835\udd61\ud835\udd5d\ud835\udd56\ud835\udd65\ud835\udd56\ud835\udd5d\ud835\udd6a \ud835\udd66\ud835\udd5f\ud835\udd63\ud835\udd56\ud835\udd52\ud835\udd55\ud835\udd52\ud835\udd53\ud835\udd5d\ud835\udd56.\n\nWe also find that text like this is incredibly common\u200a-\u200aparticularly on social media.\n\nAnother pain-point comes from diacritics (the little glyphs in \u00c7, \u00e9, \u00c5) that you'll find in almost every European language.\n\nThese characters have a hidden property that can trip up any NLP model\u200a-\u200atake a look at the Unicode for two versions of \u00c7:\n\nLatin capital letter C with cedilla: \\u00C7\n\nLatin capital letter C + combining cedilla: \\u0043\\u0327\n\nBoth are completely different, despite rendering as the same character.\n\nTo deal with all of these text variants we need to use Unicode normalization - which we will cover in this video.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/what-on-earth-is-unicode-normalization-56c005c55ad0\n\nFriend link (free access):\nhttps://towardsdatascience.com/what-on-earth-is-unicode-normalization-56c005c55ad0?sk=0cd19a9ad9f5d948b33179bab3c3b7cd", "Category": "Education", "Like Count": 43.0, "Dislike Count": 0.0}
{"Video ID": "2qJavL-VX9Y", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "The NEW Match-Case Statement in Python 3.10", "Time Created": "2021-03-17 20:37:52 UTC", "Time Published": "2021-03-19 16:00:03 UTC", "Duration": "1088 seconds", "Description": "Python 3.10 is beginning to fill-out with plenty of fascinating new features. One of those, in particular, caught my attention\u200a-\u200astructural pattern matching\u200a-\u200aor as most of us will know it, switch/case statements.\n\nSwitch-statements have been absent from Python despite being a common feature of most languages. Python is leapfrogging ahead of those languages by introducing the match-case statement as a switch-case v2.0.\n\nBack in 2006, PEP 3103 was raised, recommending the implementation of a switch-case statement. However, after a poll at PyCon 2007 received no support for the feature, the Python devs dropped it.\n\nFast-forward to 2020, and Guido van Rossum, the creator of Python, committed the first documentation showing the new match-statements, which have been named Structural Pattern Matching, as found in PEP 634.\n\nLet's take a look at how this new logic works.\n\nMedium Article:\nhttps://towardsdatascience.com/switch-case-statements-are-coming-to-python-d0caf7b2bfd3\n\nFriend Link (free access):\nhttps://towardsdatascience.com/switch-case-statements-are-coming-to-python-d0caf7b2bfd3?sk=363e0f7696502647e007f91910b4c817\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:58 Switch-Case\n02:37 Flow of Logic\n03:21 Second Example (Tuples)\n05:00 Final Example Setup\n11:30 Final Example If-Else Version\n15:22 Final Example Match-Case Version", "Category": "Education", "Like Count": 310.0, "Dislike Count": 11.0}
{"Video ID": "pjtnkCGElcE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Multi-Class Language Classification With BERT in TensorFlow", "Time Created": "2021-03-24 17:51:01 UTC", "Time Published": "2021-03-25 16:00:15 UTC", "Duration": "2604 seconds", "Description": "Chapters for each section of the video (preprocessing, model build, prediction) are in the video timeline.\n\nTransformers have been described as the fourth pillar of deep learning [1], alongside the three big neural net architectures of CNNs, RNNs, and MLPs.\n\nHowever, from the perspective of natural language processing\u200a-\u200atransformers are much more than that. Since their introduction in 2017, they've come to dominate a majority of NLP benchmarks\u200a-\u200aand continue to impress daily.\n\nWhat I'm saying is, transformers are damn cool. And with libraries like HuggingFace's transformers\u200a-\u200ait has become too easy to build incredible solutions with them.\n\nSo, what's not to love? Incredible performance paired with the ultimate ease-of-use.\n\nIn this video, we'll work through building a multi-class classification model using transformers\u200a-\u200afrom start-to-finish.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/multi-class-classification-with-transformers-6cf7b59a033a\n\nFree access:\nhttps://towardsdatascience.com/multi-class-classification-with-transformers-6cf7b59a033a?sk=544872025c2283c54cf4294814b8cae3\n\nLink to Kaggle video:\nhttps://youtu.be/DgGFhQmfxHo\n\n[1] Fourth Pillar of AI:\nhttps://ark-invest.com/articles/analyst-research/transformers-comprise-the-fourth-pillar-of-deep-learning/\n\n00:00 Intro\n01:21 Pulling Data\n01:47 Preprocessing\n14:33 Data Input Pipeline\n24:14 Defining Model\n33:29 Model Training\n35:36 Saving and Loading Models\n37:37 Making Predictions", "Category": "Education", "Like Count": 264.0, "Dislike Count": 1.0}
{"Video ID": "JkeNVaiUq_c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Python Packages for Pip", "Time Created": "2021-04-02 14:51:14 UTC", "Time Published": "2021-04-02 15:19:32 UTC", "Duration": "1267 seconds", "Description": "The most powerful feature of Python is its community. Almost every use-case out there has a package built specifically for it.\n\nNeed to send mobile/email alerts? pip install knockknock \u200a- \u200aBuild ML apps? pip install streamlit \u200a- \u200aBored of your terminal? pip install colorama\u200a - \u200aIt's too easy!\n\nI know this is obvious, but those libraries didn't magically appear. For each package, there is a person, or many persons\u200a-\u200athat actively developed and deployed that package.\n\nEvery single one.\n\nAll 300K+ of them.\n\nThat is why Python is Python, the level of support is phenomenal\u200a-\u200amindblowing.\n\nIn this video, we will learn how to build our own packages. And add them to the Python Package Index (PyPI). Afterward, we will be able to install our packages using pip install!\n\nGitHub Repo:\nhttps://github.com/jamescalam/aesthetic_ascii\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium Article:\nhttps://towardsdatascience.com/how-to-package-your-python-code-df5a7739ab2e\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/how-to-package-your-python-code-df5a7739ab2e?sk=04d9f67c0654445bbcbbf6825f535900", "Category": "Education", "Like Count": 390.0, "Dislike Count": 11.0}
{"Video ID": "4Jmq28RQ3hU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Structure a Q&A ML App", "Time Created": "2021-04-09 15:02:44 UTC", "Time Published": "2021-04-09 15:22:50 UTC", "Duration": "585 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nI'm planning on doing something different, a series of videos where we work through the steps - from start-to-finish - of (attempting) to build a Q&A web app that answers our questions with Stoic answers.\n\nIn this video, I'm outlining the idea and describing the high-level setup that I think we'll need to put together. It should be cool!\n\nWe'll be using the Haystack framework for 'Q&A at scale', which using HuggingFace transformers under-the-hood, and the Elasticsearch document store.\n\nFind the repo here:\nhttps://github.com/jamescalam/aurelius\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 46.0, "Dislike Count": 0.0}
{"Video ID": "Vwq7Ucp9UCw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Index Q&A Data With Haystack and Elasticsearch", "Time Created": "2021-04-11 21:30:32 UTC", "Time Published": "2021-04-12 15:00:11 UTC", "Duration": "807 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe second video in 'Building a Stoic Q&A App' - here we're setting up Elasticsearch and Haystack to store the data (Meditations) ready for retrieval when we ask our app questions.\n\nFind the code here:\nhttps://github.com/jamescalam/aurelius/tree/main/code/labs\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 79.0, "Dislike Count": 3.0}
{"Video ID": "DBsxUSUhfRg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Q&A Document Retrieval With DPR", "Time Created": "2021-04-12 14:44:59 UTC", "Time Published": "2021-04-15 15:00:10 UTC", "Duration": "890 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe third video in building our Stoic Q&A app.\n\nIn open-domain question answering, we typically design a model architecture that contains a data source, retriever, and reader/generator.\n\nThe first of these components is typically a document store. The two most popular stores we use here are Elasticsearch and FAISS.\n\nNext up is our retriever \u2014 the topic of this video. The job of the retriever is to filter through our document store for relevant chunks of information (the documents) and pass them to the reader/generator model.\n\nDPR (dense passage retriever) is a dense vector retriever that is trained on question-context pairs. Encoding both accordingly - enabling super accurate similarity indexing.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nIf you're interested in learning more about DPR, I wrote about it on Medium here:\nhttps://towardsdatascience.com/how-to-create-an-answer-from-a-question-with-dpr-d76e29cc5d60\n\n(Free link):\nhttps://towardsdatascience.com/how-to-create-an-answer-from-a-question-with-dpr-d76e29cc5d60?sk=1bdd7c1bff80bf51410962691c690c69\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 57.0, "Dislike Count": 0.0}
{"Video ID": "QrzHImDEq_w", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Use Type Annotations in Python", "Time Created": "2021-04-23 21:44:38 UTC", "Time Published": "2021-04-27 14:53:25 UTC", "Duration": "907 seconds", "Description": "Type annotations\u200a-\u200aalso known as type signatures\u200a-\u200aare used to indicate the datatypes of variables and input/outputs of functions and methods.\n\nIn many languages, datatypes are explicitly stated. In these languages, if you don't declare your datatype\u200a-\u200athe code will not run.\n\nType annotations have a long and convoluted history with Python, going all the way back to the first release of Python 3 with the initial implementation of function annotations.\n\nType annotations in Python are not make-or-break like in other languages (like C). They're optional chunks of syntax that we can add to make our code more explicit.\n\nErroneous type annotations will do nothing more than highlight the incorrect annotation in our code editor\u200a-\u200ano errors are ever raised due to annotations.\n\nSo, if type annotations are not enforced, why use them?\n\nWell, as we touched upon already\u200a-\u200adeclaring types makes our code more explicit, and if done well, easier to read\u200a-\u200aboth for ourselves and others.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nRead the Medium article here:\nhttps://towardsdatascience.com/type-annotations-in-python-d90990b172dc\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/type-annotations-in-python-d90990b172dc?sk=29bc29ab5478a842363963b421781b47\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:55 Datatypes Example in C\n2:53 Static and Dynamic Typed Languages\n3:47 Type Annotations in Python\n4:25 How to Define Simple Types\n6:04 IDE Warnings\n8:20 More Complex Types\n9:53 dict[str, int]\n11.07 Multiple Types\n11:38 Union Operator (Py 3.9)\n12:34 Union Operator (Py 3.10)\n13:21 Optional Operator", "Category": "Education", "Like Count": 132.0, "Dislike Count": 3.0}
{"Video ID": "2tdLYIKPafc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Extractive Q&A With Haystack and FastAPI in Python", "Time Created": "2021-04-26 22:03:55 UTC", "Time Published": "2021-04-29 15:00:04 UTC", "Duration": "1058 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nIn this video we work through building an extractive Q&A stack using Haystack, and embedding it within a FastAPI instance in Python.\n\nWe use the BERT transformer for our reader model, alongside Elasticsearch and the BM25 retriever algorithm.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 71.0, "Dislike Count": 1.0}
{"Video ID": "jVPd7lEvjtg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentence Similarity With Transformers and PyTorch (Python)", "Time Created": "2021-05-04 15:25:17 UTC", "Time Published": "2021-05-05 15:00:20 UTC", "Duration": "1270 seconds", "Description": "Easy mode: https://youtu.be/Ey81KfQ3PQU\n\nAll we ever seem to talk about nowadays are BERT this, BERT that. I want to talk about something else, but BERT is just too good \u200a- \u200aso this video will be about BERT for sentence similarity.\n\nA big part of NLP relies on similarity in highly-dimensional spaces. Typically an NLP solution will take some text, process it to create a big vector/array representing said text\u200a-\u200athen perform several transformations.\n\nIt's highly-dimensional magic.\n\nSentence similarity is one of the clearest examples of how powerful highly-dimensional magic can be.\n\nThe logic is this:\n- Take a sentence, convert it into a vector.\n- Take many other sentences, and convert them into vectors.\n- Find sentences that have the smallest distance (Euclidean) or smallest angle (cosine similarity) between them\u200a-\u200amore on that here.\n- We now have a measure of semantic similarity between sentences\u200a-\u200aeasy!\n\nAt a high level, there's not much else to it. But of course, we want to understand what is happening in a little more detail and implement this in Python too.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1?sk=c0f2990b4660210b447e52d55bd0f4e5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:16 BERT Base Network\n1:11 Sentence Vectors and Similarity\n1:47 The Data and Model\n3:01 Two Approaches\n3:16 Tokenizing Sentences\n9:11 Creating last_hidden_state Tensor\n11:08 Creating Sentence Vectors\n17:53 Cosine Similarity", "Category": "Education", "Like Count": 233.0, "Dislike Count": 2.0}
{"Video ID": "Ey81KfQ3PQU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentence Similarity With Sentence-Transformers in Python", "Time Created": "2021-05-04 19:55:42 UTC", "Time Published": "2021-05-05 15:00:09 UTC", "Duration": "370 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHard mode: https://youtu.be/jVPd7lEvjtg\n\nAll we ever seem to talk about nowadays are BERT this, BERT that. I want to talk about something else, but BERT is just too good \u200a- \u200aso this video will be about BERT for sentence similarity.\n\nA big part of NLP relies on similarity in highly-dimensional spaces. Typically an NLP solution will take some text, process it to create a big vector/array representing said text\u200a-\u200athen perform several transformations.\n\nIt's highly-dimensional magic.\n\nSentence similarity is one of the clearest examples of how powerful highly-dimensional magic can be.\n\nThe logic is this:\n- Take a sentence, convert it into a vector.\n- Take many other sentences, and convert them into vectors.\n- Find sentences that have the smallest distance (Euclidean) or smallest angle (cosine similarity) between them\u200a-\u200amore on that here.\n- We now have a measure of semantic similarity between sentences\u200a-\u200aeasy!\n\nAt a high level, there's not much else to it. But of course, we want to understand what is happening in a little more detail and implement this in Python too.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1?sk=c0f2990b4660210b447e52d55bd0f4e5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 371.0, "Dislike Count": 4.0}
{"Video ID": "W8ZPQOcHnlE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "NER With Transformers and spaCy (Python)", "Time Created": "2021-05-09 20:57:10 UTC", "Time Published": "2021-05-11 15:00:28 UTC", "Duration": "567 seconds", "Description": "Named entity recognition (NER) consists of extracting 'entities' from text\u200a-\u200awhat we mean by that is given the sentence:\n\n\"Apple reached an all-time high stock price of 143 dollars this January.\"\n\nWe might want to extract the key pieces of information\u200a-\u200aor 'entities'\u200a-\u200aand categorize each of those entities. Like so:\n\n- Apple \u200a: Organization\n- 143 dollars\u200a: \u200aMonetary Value\n- this January\u200a: \u200aDate\n\nFor us humans, this is easy. But how can we teach a machine to distinguish between a granny smith apple and the Apple we trade on NASDAQ?\n\n(No, we can't rely on the 'A' being capitalized\u2026)\n\nThis is where NER comes in\u200a-\u200ausing NER, we can extract keywords like apple and identify that it is, in fact, an organization\u200a-\u200anot a fruit.\n\nThe go-to library for NER is spaCy, which is incredible. But what if we added transformers to spaCy? Even better - we'll cover exactly that in this video.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 120.0, "Dislike Count": 2.0}
{"Video ID": "q9NS5WpfkrU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #1 - Masked-Language Modeling (MLM)", "Time Created": "2021-05-19 09:31:26 UTC", "Time Published": "2021-05-19 14:51:39 UTC", "Duration": "984 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nBERT, everyone's favorite transformer costs Google ~$7K to train (and who knows how much in R&D costs). From there, we write a couple of lines of code to use the same model\u200a-\u200aall for free.\n\nBERT has enjoyed unparalleled success in NLP thanks to two unique training approaches, masked-language modeling (MLM), and next sentence prediction (NSP).\n\nMLM consists of giving BERT a sentence and optimizing the weights inside BERT to output the same sentence on the other side.\n\nSo we input a sentence and ask that BERT outputs the same sentence.\n\nHowever, before we actually give BERT that input sentence\u200a-\u200awe mask a few tokens.\n\nSo we're actually inputting an incomplete sentence and asking BERT to complete it for us.\n\nHow to train BERT with MLM:\nhttps://youtu.be/R6hcxMMOrPE\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c?sk=17a19eca8dc8280bea4138802580ffe0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://www.udemy.com/course/nlp-with-transformers/?couponCode=MEDIUM3\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 277.0, "Dislike Count": 3.0}
{"Video ID": "R6hcxMMOrPE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #2 - Train With Masked-Language Modeling (MLM)", "Time Created": "2021-05-19 11:38:10 UTC", "Time Published": "2021-05-19 14:51:49 UTC", "Duration": "1666 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nBERT has enjoyed unparalleled success in NLP thanks to two unique training approaches, masked-language modeling (MLM), and next sentence prediction (NSP).\n\nIn many cases, we might be able to take the pre-trained BERT model out-of-the-box and apply it successfully to our own language tasks.\n\nBut often, we might need to pre-train the model for a specific use case even further.\n\nFurther training with MLM allows us to tune BERT to better understand the particular use of language in a more specific domain.\n\nOut-of-the-box BERT\u200a-\u200agreat for general purpose use. Fine-tuned with MLM BERT\u200a-\u200agreat for domain-specific use.\n\nIn this video, we'll cover exactly how to fine-tune BERT models using MLM in PyTorch.\n\n\ud83d\udc7e Code:\nhttps://github.com/jamescalam/transformers/blob/main/course/training/03_mlm_training.ipynb\n\nMeditations data:\nhttps://github.com/jamescalam/transformers/blob/main/data/text/meditations/clean.txt\n\nUnderstanding MLM:\nhttps://youtu.be/q9NS5WpfkrU\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c?sk=17a19eca8dc8280bea4138802580ffe0\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 223.0, "Dislike Count": 1.0}
{"Video ID": "1gN1snKBLP0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #3 - Next Sentence Prediction (NSP)", "Time Created": "2021-05-23 18:14:04 UTC", "Time Published": "2021-05-25 14:56:47 UTC", "Duration": "823 seconds", "Description": "Next sentence prediction (NSP) is one-half of the training process behind the BERT model (the other being masked-language modeling\u200a-\u200aMLM).\n\nWhere MLM teaches BERT to understand relationships between words\u200a-\u200aNSP teaches BERT to understand relationships between sentences.\n\nIn the original BERT paper, it was found that without NSP, BERT performed worse on every single metric - \u200aso it's important.\n\nNow, when we use a pre-trained BERT model, training with NSP and MLM has already been done, so why do we need to know about it?\n\nWell, we can actually further pre-train these pre-trained BERT models so that they better understand the language used in our specific use-cases. To do that, we can use both MLM and NSP.\n\nSo, in this video, we'll go into depth on what NSP is, how it works, and how we can implement it in code.\n\nTraining with NSP:\nhttps://youtu.be/x1lAcT3xl5M\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f?sk=3595968413abde1c5833e1a96e449673\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 94.0, "Dislike Count": 6.0}
{"Video ID": "x1lAcT3xl5M", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #4 - Train With Next Sentence Prediction (NSP)", "Time Created": "2021-05-27 15:52:57 UTC", "Time Published": "2021-05-27 16:15:39 UTC", "Duration": "2205 seconds", "Description": "Next sentence prediction (NSP) is one-half of the training process behind the BERT model (the other being masked-language modeling\u200a-\u200aMLM).\n\nAlthough NSP (and MLM) are used to pre-train BERT models, we can use these exact methods to further pre-train our models to better understand the specific style of language in our own use cases.\n\nSo, in this video, we'll cover exactly how we take an unstructured body of text, and use it to pre-train a BERT model using NSP.\n\nMeditations data:\nhttps://github.com/jamescalam/transformers/blob/main/data/text/meditations/clean.txt\n\nJupyter Notebook\nhttps://github.com/jamescalam/transformers/blob/main/course/training/06_nsp_training.ipynb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f?sk=3595968413abde1c5833e1a96e449673\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 95.0, "Dislike Count": 1.0}
{"Video ID": "5-A435hIYio", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "New Features in Python 3.10", "Time Created": "2021-06-03 16:41:56 UTC", "Time Published": "2021-06-08 15:00:02 UTC", "Duration": "800 seconds", "Description": "The Python 3.10 release has several new features like structural pattern matching, a new typing Union operator, and parenthesized context managers!\n\nPython 3.10 has now been released, here we test all of the best new features introduced.\n\nWe'll cover some of the most interesting additions to Python\u200a-\u200astructural pattern matching, parenthesized context managers, more typing, and the new and improved error messages.\n\nDownload the latest release:\nhttps://www.python.org/downloads/release/python-3100/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/whats-new-in-python-3-10-a757c6c69342\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/whats-new-in-python-3-10-a757c6c69342?sk=648ae12c1025a83affba4eecec0d46c6\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:45 Type Annotations in Python\n01:10  Typing Union Operator\n02:07 Parenthesized Context Managers\n05:07 Structural Pattern Matching\n09:31 Better Error Messages", "Category": "Education", "Like Count": 375.0, "Dislike Count": 2.0}
{"Video ID": "IC9FaVPKlYc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #5 - Training With BertForPretraining", "Time Created": "2021-06-04 05:13:06 UTC", "Time Published": "2021-06-15 15:00:19 UTC", "Duration": "1306 seconds", "Description": "NSP Logic\nhttps://youtu.be/1gN1snKBLP0\n\nMLM Logic\nhttps://youtu.be/q9NS5WpfkrU\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-bert-aaad00533168\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/how-to-train-bert-aaad00533168?sk=5ad4e5e44a6c573b3be1967c9abdcc35\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 128.0, "Dislike Count": 1.0}
{"Video ID": "fA0dFQacmic", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "FREE 11 Hour NLP Transformers Course (Next 3 Days Only)", "Time Created": "2021-06-04 07:56:44 UTC", "Time Published": "2021-06-04 13:00:19 UTC", "Duration": "267 seconds", "Description": "The offer has now expired! You can find the final 70% discount here:\nhttps://bit.ly/3DFvvY5\n\nIn total, 10823 people redeemed the code - which is incredible, I'm very happy so many of you were interested in the course and I hope it will help many of you in learning about transformers and NLP where it may have been too expensive to otherwise - so thank you all!\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 51.0, "Dislike Count": 0.0}
{"Video ID": "GhGUZrcB-WM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Use HuggingFace's Datasets - Transformers From Scratch #1", "Time Created": "2021-06-21 21:56:31 UTC", "Time Published": "2021-06-22 13:00:07 UTC", "Duration": "861 seconds", "Description": "How can we build our own custom transformer models?\n\nMaybe we'd like our model to understand a less common language, how many transformer models out there have been trained on Piemontese or the Nahuatl languages?\n\nIn that case, we need to do something different. We need to build our own model\u200a-\u200afrom scratch.\n\nIn this video, we'll learn how to use HuggingFace's datasets library to download multilingual data and prepare it for training our custom transformer tokenizer and model.\n\n---\nPart 2: https://youtu.be/JIeAB8vvBQo\nPart 3: https://youtu.be/heTYbpr9mD8\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403?sk=aea909609f41be43bdb2dbbd75a801f2\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 147.0, "Dislike Count": 3.0}
{"Video ID": "JIeAB8vvBQo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Build a Custom Transformer Tokenizer - Transformers From Scratch #2", "Time Created": "2021-06-22 20:07:37 UTC", "Time Published": "2021-06-24 14:00:06 UTC", "Duration": "857 seconds", "Description": "How can we build our own custom transformer models?\n\nMaybe we'd like our model to understand a less common language, how many transformer models out there have been trained on Piemontese or the Nahuatl languages?\n\nIn that case, we need to do something different. We need to build our own model\u200a-\u200afrom scratch.\n\nIn this video, we'll learn how to use HuggingFace's tokenizers library to build our own custom transformer tokenizer.\n\nPart 1: https://youtu.be/GhGUZrcB-WM\n---\nPart 3: https://youtu.be/heTYbpr9mD8\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403?sk=aea909609f41be43bdb2dbbd75a801f2\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 80.0, "Dislike Count": 3.0}
{"Video ID": "ziiF1eFM3_4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)", "Time Created": "2021-06-28 13:25:28 UTC", "Time Published": "2021-06-29 13:00:23 UTC", "Duration": "1764 seconds", "Description": "Vector similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together.\n\nSimilarity search is a complex topic and there are countless techniques for building effective search engines.\n\nIn this video, we'll cover three vector-based approaches for comparing languages and identifying similar 'documents', covering both vector similarity search and semantic search:\n\n- TF-IDF\n- BM25\n- Sentence-BERT\n\n\ud83d\udcf0 Original article:\nhttps://www.pinecone.io/learn/semantic-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n01:37 TF-IDF\n11:44 BM25\n20:30 SBERT", "Category": "Education", "Like Count": 416.0, "Dislike Count": 1.0}
{"Video ID": "AY62z7HrghY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)", "Time Created": "2021-06-28 17:44:01 UTC", "Time Published": "2021-06-29 12:00:04 UTC", "Duration": "1520 seconds", "Description": "Similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together.\n\nSimilarity search is a complex topic and there are countless techniques for building effective search engines.\n\nIn this video, we'll cover three traditional approaches for comparing languages and identifying similar 'documents':\n\n- Jaccard Similarity\n- w-shingling\n- Levenshtein distance\n\n\ud83d\udcf0 Original article:\nhttps://www.pinecone.io/learn/semantic-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:23 Jaccard Similarity\n02:39 w-shingling\n07:17 Levenshtein Distance", "Category": "Education", "Like Count": 86.0, "Dislike Count": 0.0}
{"Video ID": "heTYbpr9mD8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building MLM Training Input Pipeline - Transformers From Scratch #3", "Time Created": "2021-07-02 15:28:46 UTC", "Time Published": "2021-07-05 14:00:30 UTC", "Duration": "1392 seconds", "Description": "The input pipeline of our training process is the more complex part of the entire transformer build. It consists of us taking our raw OSCAR training data, transforming it, and preparing it for Masked-Language Modeling (MLM). Finally, we load our data into a DataLoader ready for training!\n\nPart 1: https://youtu.be/GhGUZrcB-WM\nPart 2: https://youtu.be/JIeAB8vvBQo\n---\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6\n\n\ud83d\udcd6 Free link:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6?sk=9db6224efbd4ec6fd407a80b528e69b0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 69.0, "Dislike Count": 0.0}
{"Video ID": "ee71R4Cqb5o", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Angular App Setup With Material - Stoic Q&A #5", "Time Created": "2021-07-05 08:50:04 UTC", "Time Published": "2021-07-20 14:00:28 UTC", "Duration": "814 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe fifth video in our Stoic Q&A series - setting up our Angular app with Angular Material.\n\nPrerequisites:\nInstallation of Node.js and NPM - https://nodejs.org/en/\nAngular - https://angular.io/guide/setup-local\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 17.0, "Dislike Count": 0.0}
{"Video ID": "35Pdoyi6ZoQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training and Testing an Italian BERT - Transformers From Scratch #4", "Time Created": "2021-07-05 18:22:41 UTC", "Time Published": "2021-07-06 13:00:03 UTC", "Duration": "1838 seconds", "Description": "We need two things for training, our DataLoader and a model. The DataLoader we have \u2014 but no model.\n\nFor training, we need a raw (not pre-trained) RobertaForMaskedLM. To create that, we first need to create a RoBERTa config object to describe the parameters we\u2019d like to initialize FiliBERTo with.\n\nOnce we have our model, we set up our training loop and train!\n\nPost-training, we'll test the model with Laura, who is Italian - and hope for the best.\n\nPart 1: https://youtu.be/GhGUZrcB-WM\nPart 2: https://youtu.be/JIeAB8vvBQo\nPart 3: https://youtu.be/heTYbpr9mD8\n---\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6?sk=9db6224efbd4ec6fd407a80b528e69b0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:35 Review of Code\n02:02 Config Object\n06:28 Setup For Training\n10:30 Training Loop\n14:57 Dealing With CUDA Errors\n16:17 Training Results\n19:52 Loss\n21:18 Fill-mask Pipeline For Testing\n21:54 Testing With Laura", "Category": "Science & Technology", "Like Count": 94.0, "Dislike Count": 1.0}
{"Video ID": "sKyvsdEv6rk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Faiss - Introduction to Similarity Search", "Time Created": "2021-07-09 13:47:26 UTC", "Time Published": "2021-07-13 15:00:19 UTC", "Duration": "1896 seconds", "Description": "Full Similarity Search Playlist:\nhttps://www.youtube.com/watch?v=AY62z7HrghY&list=PLIUOU7oqGTLhlWpTz4NnuT3FekouIVlqc&index=1\n\nFacebook AI Similarity Search (FAISS) is one of the most popular implementations of efficient similarity search, but what is it\u200a-\u200aand how can we use it?\n\nWhat is it that makes FAISS special? How do we make the best use of this incredible tool?\n\nFortunately, it's a brilliantly simple process to get started with. And in this video, we'll explore some of the options FAISS provides, how they work, and\u200a-\u200amost importantly\u200a-\u200ahow FAISS can make our semantic search faster.\n\n\ud83c\udf32 Pinecone Article:\nhttps://www.pinecone.io/learn/faiss-tutorial/\n\n\ud83d\udcca Data:\nhttps://github.com/jamescalam/data/tree/main/sentence_embeddings_15K\n\nNotebook:\nhttps://gist.github.com/jamescalam/7117aa92235a7f52141ad0654795aa48\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 354.0, "Dislike Count": 5.0}
{"Video ID": "bWLvGGJLzF8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Why are there so many Tokenization methods in HF Transformers?", "Time Created": "2021-07-27 07:12:07 UTC", "Time Published": "2021-07-27 14:00:10 UTC", "Duration": "1080 seconds", "Description": "HuggingFace's transformers library is the de-facto standard for NLP\u200a-\u200aused by practitioners worldwide, it's powerful, flexible, and easy to use. It achieves this through a fairly large (and complex) code-base, which has resulted in the question:\n\n\"Why are there so many tokenization methods in HuggingFace transformers?\"\n\nTokenization is the process of encoding a string of text into transformer-readable token ID integers. In this video we cover five different methods for this - do these all produce the same output, or is there a difference between them?\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/why-are-there-so-many-tokenization-methods-for-transformers-a340e493b3a8\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/why-are-there-so-many-tokenization-methods-for-transformers-a340e493b3a8?sk=4a7e8c88d331aef9103e153b5b799ff5\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 51.0, "Dislike Count": 0.0}
{"Video ID": "B7wmo_NImgM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Choosing Indexes for Similarity Search (Faiss in Python)", "Time Created": "2021-08-09 14:33:47 UTC", "Time Published": "2021-08-09 15:04:10 UTC", "Duration": "1893 seconds", "Description": "Facebook AI Similarity Search (Faiss) is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles\u200a-\u200awith incredible accuracy in sub-second timescales for billion+ size datasets.\n\nThe success in Faiss is due to many reasons. One of those, in particular, is its flexibility. Faiss recognizes that there is no 'one-size-fits-all' in similarity search.\n\nInstead, Faiss comes with a wide range of search indexes\u200a-\u200awhich we can mix and match to our choosing.\n\nHowever, this great flexibility produces a question\u200a-\u200ahow do we know which size fits our use case?\n\nWhich index do we choose? Should we use multiple indexes, or is one enough?\n\nThis video will explore the pros and cons of some of the most important indexes\u200a-\u200aFlat, LSH, HNSW, and IVF. We will learn how we decide which to use and the impact of parameters in each index to build some of the best indexes for semantic search.\n\n\ud83c\udf32 Pinecone Article:\nhttps://www.pinecone.io/learn/vector-indexes/\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nDownload script for Sift1M dataset:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nSimilarity Search Series:\nhttps://www.youtube.com/playlist?list=PLIUOU7oqGTLhlWpTz4NnuT3FekouIVlqc\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 122.0, "Dislike Count": 1.0}
{"Video ID": "e_SBq3s20M8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)", "Time Created": "2021-08-19 16:53:50 UTC", "Time Published": "2021-08-20 16:00:16 UTC", "Duration": "1627 seconds", "Description": "Locality sensitive hashing (LSH) is a widely popular technique used in approximate nearest neighbor (ANN) search. The solution to efficient similarity search is a profitable one\u200a-\u200ait is at the core of several billion (and even trillion) dollar companies.\n\nLSH consists of a variety of different methods. In this video, we'll be covering the traditional approach\u200a-\u200awhich consists of multiple steps\u200a-\u200ashingling, MinHashing, and the final banded LSH function.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n01:21 Overview\n05:58 Shingling\n08:45 Vocab\n09:27 One-hot Encoding\n11:10 MinHash\n15:51 Signature Info\n18:08 LSH\n22:20 Tuning LSH", "Category": "Science & Technology", "Like Count": 208.0, "Dislike Count": 19.0}
{"Video ID": "8bOrMqEdfiQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How LSH Random Projection works in search (+Python)", "Time Created": "2021-08-24 05:09:11 UTC", "Time Published": "2021-08-24 16:00:04 UTC", "Duration": "1148 seconds", "Description": "Locality sensitive hashing (LSH) is a widely popular technique used in approximate similarity search. The solution to efficient similarity search is a profitable one\u200a-\u200ait is at the core of several billion (and even trillion) dollar companies.\n\nThe problem with similarity search is scale. Many companies deal with millions-to-billions of data points every single day. Given a billion data points, is it feasible to compare all of them with every search?\n\nFurther, many companies are not performing single searches\u200a-\u200aGoogle deals with more than 3.8 million searches every minute.\n\nBillions of data points combined with high-frequency searches are problematic\u200a-\u200aand we haven't considered the dimensionality nor the similarity function itself. Clearly, an exhaustive search across all data points is unrealistic for larger datasets.\n\nThe solution to searching impossibly huge datasets? Approximate search. Rather than exhaustively comparing every pair, we approximate\u200a-\u200arestricting the search scope only to high probability matches.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing-random-projection/\n\nDownload Sift1M:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nIndexLSH for Fast Similarity Search in Faiss:\nhttps://youtu.be/ZLfdQq_u7Eo\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 66.0, "Dislike Count": 3.0}
{"Video ID": "ZLfdQq_u7Eo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "IndexLSH for Fast Similarity Search in Faiss", "Time Created": "2021-08-24 05:25:21 UTC", "Time Published": "2021-08-24 16:00:12 UTC", "Duration": "1119 seconds", "Description": "Faiss \u200a- \u200aor Facebook AI Similarity Search\u200a - \u200ais an open-source framework built for enabling similarity search.\n\nFaiss has many super-efficient implementations of different indexes that we can use in similarity search. That long list of indexes includes IndexLSH\u200a-\u200aan easy-to-use implementation of everything we have covered so far in LSH.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing-random-projection/\n\nDownload Sift1M:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nHow LSH Random Projection works in search (+Python):\nhttps://youtu.be/8bOrMqEdfiQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 27.0, "Dislike Count": 0.0}
{"Video ID": "BMYBwbkbVec", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Faiss - Vector Compression with PQ and IVFPQ (in Python)", "Time Created": "2021-08-30 14:35:01 UTC", "Time Published": "2021-08-30 15:30:04 UTC", "Duration": "1161 seconds", "Description": "So far we\u2019ve worked through the logic behind a simple, readable implementation of product quantization (PQ) in Python for semantic search. Realistically we wouldn\u2019t use this because it is not optimized and we already have excellent implementations elsewhere. Instead, we would use a library like Faiss (Facebook AI Similarity Search) \u2014 or a production-ready service like Pinecone.\n\nWe\u2019ll take a look at how we can build a PQ index in Faiss, and we\u2019ll even take a look at combining PQ with an Inverted File (IVF) step to improve search speed.\n\nBefore we start, we need to get data. We will be using the Sift1M dataset. It can be downloaded and opened using this script:\nhttps://gist.github.com/jamescalam/928a374b85daffa49a565f3dc18d059c#file-get_sift1m-ipynb\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/product-quantization/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 36.0, "Dislike Count": 1.0}
{"Video ID": "t9mRf2S5vDI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Product Quantization for Vector Similarity Search (+ Python)", "Time Created": "2021-08-30 15:22:47 UTC", "Time Published": "2021-08-30 15:37:46 UTC", "Duration": "1777 seconds", "Description": "Vector similarity search can require huge amounts of memory. Indexes containing 1M dense vectors (a small dataset in today\u2019s world) will often require several GBs of memory to store. When building recommendation systems or semantic search engines, this is not acceptable.\n\nThe problem of excessive memory usage is exasperated by high-dimensional data, and with ever-increasing dataset sizes, this can very quickly become unmanageable.\n\nProduct quantization (PQ) is a popular method for dramatically compressing high-dimensional vectors to use 97% less memory, and for making nearest-neighbor search speeds 5.5x faster in our tests.\n\nA composite IVF+PQ index speeds up the search by another 16.5x without affecting accuracy, for a whopping total speed increase of 92x compared to non-quantized indexes.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/product-quantization/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 116.0, "Dislike Count": 2.0}
{"Video ID": "GEhmmcx1lvM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Composite Indexes and the Faiss Index Factory", "Time Created": "2021-09-11 17:27:12 UTC", "Time Published": "2021-09-24 12:53:58 UTC", "Duration": "1063 seconds", "Description": "In the world of vector search, there are many indexing methods and vector processing techniques that allow us to prioritize between recall, latency, and memory usage.\n\nUsing specific methods such as IVF, PQ, or HNSW, we can often return good results. But for best performance we will usually want to use composite indexes.\n\nWe can view a composite index as a step-by-step process of vector transformations and one or more indexing methods. Allowing us to place multiple indexes and/or processing steps together to create our \u2018ideal\u2019 index.\n\nFor example, we can use an inverted file (IVF) index to reduce the scope of our search (increasing search speed), and then add a compression technique such as product quantization (PQ) to keep larger indexes within a reasonable size limit.\n\nWhere there is the ability to customize indexes, there is the risk of producing indexes with unnecessarily poor recall, latency, or memory usage.\n\nWe must know how composite indexes work if we want to build robust and high-performance vector similarity search applications. It is essential to understand where different indexes or vector transformations can be used \u2014 and when they are not needed.\n\nPart 2: https://youtu.be/3Wqh4iUupbM\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/composite-indexes/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:54 Composite Indexes\n06:43 Faiss Index Factory\n11:34 Why we use Index Factory\n17:11 Outro", "Category": "Science & Technology", "Like Count": 21.0, "Dislike Count": 0.0}
{"Video ID": "3Wqh4iUupbM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Best Indexes for Similarity Search in Faiss", "Time Created": "2021-09-12 07:02:26 UTC", "Time Published": "2021-09-24 12:54:07 UTC", "Duration": "1582 seconds", "Description": "In the world of vector search, there are many indexing methods and vector processing techniques that allow us to prioritize between recall, latency, and memory usage.\n\nUsing specific methods such as IVF, PQ, or HNSW, we can often return good results. But for best performance we will usually want to use composite indexes.\n\nWe can view a composite index as a step-by-step process of vector transformations and one or more indexing methods. Allowing us to place multiple indexes and/or processing steps together to create our \u2018ideal\u2019 index.\n\nFor example, we can use an inverted file (IVF) index to reduce the scope of our search (increasing search speed), and then add a compression technique such as product quantization (PQ) to keep larger indexes within a reasonable size limit.\n\nWhere there is the ability to customize indexes, there is the risk of producing indexes with unnecessarily poor recall, latency, or memory usage.\n\nWe must know how composite indexes work if we want to build robust and high-performance vector similarity search applications. It is essential to understand where different indexes or vector transformations can be used \u2014 and when they are not needed.\n\nPart 1: https://youtu.be/GEhmmcx1lvM\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/composite-indexes/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:30 IVFADC\n03:30 IVFADC in Faiss\n07:29 Multi-D-ADC\n09:17 Multi-D-ADC in Faiss\n14:43 IVF-HNSW\n21:39 IVF-HNSW in Faiss\n25:58 Outro", "Category": "Science & Technology", "Like Count": 31.0, "Dislike Count": 0.0}
{"Video ID": "cR4qMSIvX28", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build a Bert WordPiece Tokenizer in Python and HuggingFace", "Time Created": "2021-09-13 20:13:08 UTC", "Time Published": "2021-09-14 13:30:06 UTC", "Duration": "1880 seconds", "Description": "Building a transformer model from scratch can often be the only option for many more specific use cases. Although BERT and other transformer models have been pre-trained for a vast number of languages and domains, they do not cover everything.\n\nOften, it is these less common use cases that stand to gain the most from having someone come along and build a specific transformer model. It could be for an uncommon language or less tech-savvy domain.\n\nBERT is the most popular transformer for a wide range of language-based machine learning\u200a-\u200afrom sentiment analysis to question and answering, BERT has enabled a diverse range of innovation across many borders and industries.\n\nThe first step for many in designing a new BERT model is the tokenizer. In this article, we'll take a look at the WordPiece tokenizer used by BERT\u200a-\u200aand see how we can build our own from scratch.\n\n\ud83d\udcd5 Medium article:\nhttps://towardsdatascience.com/how-to-build-a-wordpiece-tokenizer-for-bert-f505d97dddbb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free Article link (if you don't have Medium membership): \nhttps://towardsdatascience.com/how-to-build-a-wordpiece-tokenizer-for-bert-f505d97dddbb?sk=eea06e01c9faecd939e10589e9de1291", "Category": "Science & Technology", "Like Count": 95.0, "Dislike Count": 1.0}
{"Video ID": "H_kJDHvu-v8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Metadata Filtering for Vector Search + Latest Filter Tech", "Time Created": "2021-09-20 12:23:11 UTC", "Time Published": "2021-09-20 14:04:27 UTC", "Duration": "2054 seconds", "Description": "Vector similarity search makes massive datasets searchable in fractions of a second. Yet despite the brilliance and utility of this technology, often what seem to be the most straightforward problems are the most difficult to solve. Such as filtering.\n\nFiltering takes the top place in being seemingly simple \u2014 but actually incredibly complex. Applying fast-but-accurate filters when performing a vector search (ie, nearest-neighbor search) on massive datasets is a surprisingly stubborn problem.\n\nThis article explains the two common methods for adding filters to vector search, and their serious limitations. Then we will explore Pinecone\u2019s solution to filtering in vector search.\n\n\ud83d\udce3 Get the API key!\nhttps://www.pinecone.io/start/\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/vector-search-filtering/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:24 Vector Search Recap\n02:03 Why Filter?\n02:56 Metadata Filtering 101\n07:48 Pre-filtering\n09:37 Post-filtering\n11:30 Single-Stage Filtering\n12:22 Vectors and Metadata Code\n13:58 Connecting to Pinecone\n14:55 Building Query Vector\n16:47 Querying\n21:37 First Filter\n24:40 Adding More Conditions\n27:03 Filtering with Numbers\n30:55 Search Speed and Filtering\n33:44 Outro", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "r-zQQ16wTCA", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Build NLP Pipelines with HuggingFace Datasets", "Time Created": "2021-09-20 14:58:03 UTC", "Time Published": "2021-09-23 13:30:07 UTC", "Duration": "2030 seconds", "Description": "HF Datasets is an essential tool for NLP practitioners\u200a-\u200ahosting over 1.4K (mostly) high-quality language-focused datasets, and an easy-to-use treasure trove of functions for building efficient pre-processing pipelines.\n\nIn this article, we will take a look at the massive repository of datasets available, and explore some of the library's brilliant data processing capabilities.\n\n\ud83d\udcd5 Medium article:\nhttps://towardsdatascience.com/build-nlp-pipelines-with-huggingface-datasets-d597ff5f68ad\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free Article Access (if you don't have Medium membership!): \nhttps://towardsdatascience.com/build-nlp-pipelines-with-huggingface-datasets-d597ff5f68ad?sk=948106e47e64bc3e9e8a1358b0568d48", "Category": "Science & Technology", "Like Count": 53.0, "Dislike Count": 1.0}
{"Video ID": "QvKMwLjdK-s", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "HNSW for Vector Search Explained and Implemented with Faiss (Python)", "Time Created": "2021-09-29 08:13:49 UTC", "Time Published": "2021-10-05 13:00:23 UTC", "Duration": "2075 seconds", "Description": "Hierarchical Navigable Small World (HNSW) graphs are among the top-performing indexes for vector similarity search. HNSW is a hugely popular technology that time and time again produces state-of-the-art performance with super-fast search speeds and flawless recall \u2014 HNSW is not to be missed.\n\nDespite being a popular and robust algorithm for approximate nearest neighbors (ANN) searches, understanding how it works is far from easy.\n\nThis video helps demystify HNSW and explains this intelligent algorithm in an easy-to-understand way. Towards the end of the video, we'll look at how to implement HNSW using Faiss and which parameter settings give us the performance we need.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/hnsw/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:41 Foundations of HNSW\n08:41 How HNSW Works\n16:38 The Basics of HNSW in Faiss\n21:40 How Faiss Builds an HNSW Graph\n26.49 Building the Best HNSW Index\n33:33 Fine-tuning HNSW\n34:30 Outro", "Category": "Science & Technology", "Like Count": 131.0, "Dislike Count": 3.0}
{"Video ID": "g_yMowQikOE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to APIs in Python - API Series #1", "Time Created": "2021-09-29 12:21:47 UTC", "Time Published": "2021-09-29 14:00:18 UTC", "Duration": "1704 seconds", "Description": "Taking those first steps into interacting with the web using Python can seem daunting\u200a-\u200abut it need not be. It is a surprisingly simple process, with well established rules and guidelines.\n\nWe'll cover the absolute essentials for getting started, including:\n\n- Application Program Interfaces (APIs)\n- Javascript Object Notation (JSON)\n- Requests with Python\n- Real world use-cases\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/quick-fire-guide-to-apis-in-python-891dd98c8877\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free Access Link (if you don't have Medium membership): \nhttps://towardsdatascience.com/quick-fire-guide-to-apis-in-python-891dd98c8877?sk=7c159ba45154db23abcc6a7f9de4f910\n\nGeocoding Docs:\nhttps://developers.google.com/maps/documentation/geocoding/cloud-setup\n\nGitHub Docs:\nhttps://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token\n\n00:00 Intro\n00:20 What is an API?\n01:47 RESTful APIs\n05:26 API Methods\n07:20 HTTP Codes (200s)\n08:14 HTTP Codes (400s)\n10:00 JSON Format\n11:21 Talking to APIs in Python\n14:30 Google Geocoding API\n22:08 GitHub API\n27:48 Outro", "Category": "Science & Technology", "Like Count": 119.0, "Dislike Count": 0.0}
{"Video ID": "bVZJ_O_-0RE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to Dense Vectors for NLP and Vision", "Time Created": "2021-10-04 08:28:38 UTC", "Time Published": "2021-10-12 17:47:15 UTC", "Duration": "2629 seconds", "Description": "There is perhaps no greater component to the success of modern Natural Language Processing (NLP) technology than vector representations of language. The meteoric early 2010s rise of NLP was ignited with the introduction of word2vec by a team lead by Tom\u00e1\u0161 Mikolov in 2013.\n\nWord2vec is one of the most iconic and earliest examples of dense vectors representing text. But since the days of word2vec, developments in representing language have advanced at ludicrous speeds.\n\nThis video will explore *why* we use dense vectors \u2014 and some of the best approaches to building dense vectors available today.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/dense-vector-embeddings-nlp/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:50 Why Dense Vectors?\n03:55 Word2vec and Representing Meaning\n08:40 Sentence Transformers\n09:58 Sentence Transformers in Python\n15:08 Question-Answering\n18:18 DPR in Python\n29:55 Vision Transformers\n33:22 OpenAI's CLIP in Python\n42:49 Review and What's Next", "Category": "Science & Technology", "Like Count": 92.0, "Dislike Count": 0.0}
{"Video ID": "MF75aNH3Gjs", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "API Series #2 - Building an API with Flask in Python", "Time Created": "2021-10-05 07:01:25 UTC", "Time Published": "2021-10-07 14:52:32 UTC", "Duration": "1902 seconds", "Description": "Next video - how to deploy to the cloud: https://youtu.be/3fsIcMgUOY8\n\nHow can we set up a way to communicate from one software instance to another? It sounds simple, and \u2014 to be completely honest \u2014 it is.\n\nAll we need is an API.\n\nAn API (Application Programming Interface) is a simple interface that defines the types of requests (demands/questions, etc.) that can be made, how they are made, and how they are processed.\n\nIn our case, we will be building an API that allows us to send a range of GET/POST/PUT/PATCH/DELETE requests (more on this later), to different endpoints, and return or modify data connected to our API.\n\nWe will be using the Flask framework to create our API and Insomnia to test it.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Medium article:\nhttps://towardsdatascience.com/the-right-way-to-build-an-api-with-python-cd08ab285f8f\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\nFree article link: \nhttps://towardsdatascience.com/the-right-way-to-build-an-api-with-python-cd08ab285f8f?sk=6e2dda4c8b6012767114e12ff34b1464\n\nDownload Insomnia:\nhttps://insomnia.rest/download", "Category": "Science & Technology", "Like Count": 117.0, "Dislike Count": 2.0}
{"Video ID": "WS1uVMGhlWQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to Sentence Embeddings with Transformers", "Time Created": "2021-10-19 09:44:58 UTC", "Time Published": "2021-10-20 17:06:20 UTC", "Duration": "1866 seconds", "Description": "Transformers have wholly rebuilt the landscape of natural language processing (NLP). Before transformers, we had okay translation and language classification thanks to recurrent neural nets (RNNs) \u2014 their language comprehension was limited and led to many minor mistakes, and coherence over larger chunks of text was practically impossible.\n\nSince the introduction of the first transformer model in the 2017 paper \u2018Attention is all you need\u2019, NLP has moved from RNNs to models like BERT and GPT. These new models can answer questions, write articles (maybe GPT-3 wrote this), enable incredibly intuitive semantic search \u2014 and much more.\n\nIn this video, we will explore how these embeddings have been adapted and applied to a range of semantic similarity applications by using a new breed of transformers called \u2018sentence transformers\u2019.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/sentence-embeddings/\n\nVectors in ML:\nhttps://www.youtube.com/playlist?list=PLIUOU7oqGTLgz-BI8bNMVGwQxIMuQddJO\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 188.0, "Dislike Count": 1.0}
{"Video ID": "aSx0jg9ZILo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fine-tune Sentence Transformers the OG Way (with NLI Softmax loss)", "Time Created": "2021-10-22 14:16:49 UTC", "Time Published": "2021-10-22 14:39:46 UTC", "Duration": "2223 seconds", "Description": "Sentence embeddings with transformers can be used across a range of applications, such as semantic textual similarity (STS), semantic clustering, or information retrieval (IR) using concepts rather than words.\n\nThis video dives deeper into the training process of the first sentence transformer, sentence-BERT, or more commonly known as SBERT. We will explore the Natural Language Inference (NLI) training approach of softmax loss to fine-tune models for producing sentence embeddings.\n\nBe aware that softmax loss is no longer the preferred approach to training sentence transformers and has been superseded by other methods such as MSE margin and multiple negatives ranking loss. But we\u2019re covering this training method as an important milestone in the development of ever-improving sentence embeddings.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/train-sentence-transformers-softmax/\n\nCheck out the Sentence Transformers library:\nhttps://github.com/UKPLab/sentence-transformers\n\nTalk by Nils Reimers (one of the SBERT creators) on training:\nhttps://www.youtube.com/watch?v=RHXZKUr8qOY\n\nHe does more NLP vids too:\nhttps://www.youtube.com/channel/UC1zCuTrfpjT6Sv2kJk-JkvA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:42 NLI Fine-tuning\n01:44 Softmax Loss Training Overview\n05:47 Preprocessing NLI Data\n12:48 PyTorch Process\n19:48 Using Sentence-Transformers\n30:45 Results\n35:49 Outro", "Category": "Science & Technology", "Like Count": 83.0, "Dislike Count": 0.0}
{"Video ID": "or5ew7dqA-c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fine-tune High Performance Sentence Transformers (with Multiple Negatives Ranking)", "Time Created": "2021-10-25 20:18:30 UTC", "Time Published": "2021-10-26 13:00:22 UTC", "Duration": "2213 seconds", "Description": "Transformer-produced sentence embeddings have come a long way in a very short time. Starting with the slow but accurate similarity prediction of BERT cross-encoders, the world of sentence embeddings was ignited with the introduction of SBERT in 2019. Since then, many more sentence transformers have been introduced. These models quickly made the original SBERT obsolete.\n\nHow did these newer sentence transformers manage to outperform SBERT so quickly? The answer is multiple negatives ranking (MNR) loss.\n\nThis video will cover what MNR loss is, the data it requires, and how to implement it to fine-tune our own high-quality sentence transformers.\n\nImplementation will cover two approaches. The first is more involved, and outlines the exact steps to fine-tune the model (we'll just run over it quickly). The second approach makes use of the sentence-transformers library\u2019s excellent utilities for fine-tuning.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/fine-tune-sentence-transformers-mnr/\n\nCheck out the Sentence Transformers library:\nhttps://github.com/UKPLab/sentence-transformers\n\nTalk by Nils Reimers (one of the SBERT creators) on training:\nhttps://www.youtube.com/watch?v=RHXZKUr8qOY\n\nHe does more NLP vids too:\nhttps://www.youtube.com/channel/UC1zCuTrfpjT6Sv2kJk-JkvA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:02 NLI Training Data\n02:56 Preprocessing\n10:11 SBERT Finetuning Visuals\n14:14 MNR Loss Visual\n16:37 MNR in PyTorch\n23:04 MNR in Sentence Transformers\n34:20 Results\n36:14 Outro", "Category": "Science & Technology", "Like Count": 86.0, "Dislike Count": 0.0}
{"Video ID": "iCkftKsnQgg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hybrid Search Walkthrough in Pinecone", "Time Created": "2021-10-29 01:44:06 UTC", "Time Published": "2021-10-29 15:05:00 UTC", "Duration": "1040 seconds", "Description": "Pinecone offers a production-ready vector database for high performance and reliable *semantic search* at scale. But did you know Pinecone's semantic search can be paired with the more traditional keyword search?\n\nSemantic search is a compelling technology allowing us to search using abstract concepts and *meaning* rather than relying on specific words. However, sometimes a simple keyword search can be just as valuable \u2014 especially if we know the exact wording of what we're searching for.\n\nIn this video, we will explore these features through a start-to-finish example of basic keyword search in Pinecone.\n\n\ud83c\udf32 Check the docs:\nhttps://www.pinecone.io/docs/examples/basic-hybrid-search/\n\n\ud83d\udd11 Free API key:\nhttps://app.pinecone.io\n\n00:52 How Hybrid Search Works\n01:25 Preprocessing\n03:01 Creating Keywords\n05:34 Creating an Index\n06:50 Data Upsert\n08:33 Query Setup\n10:52 Keyword Search\n12:31 OR Logic\n14:49 AND Logic\n15:10 Negation\n17:04 Outro", "Category": "Science & Technology", "Like Count": 17.0, "Dislike Count": 1.0}
{"Video ID": "3fsIcMgUOY8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "API Series #3 - How to Deploy Flask APIs to the Cloud (GCP)", "Time Created": "2021-11-01 23:16:31 UTC", "Time Published": "2021-11-02 14:30:00 UTC", "Duration": "806 seconds", "Description": "Building that first API is for many of us, a significant step towards creating impactful tools that may one day be used by many developers. But often those APIs don't make it out of our local machines.\n\nFortunately, it's incredibly easy to deploy APIs. Assuming you have no idea what you're doing right now\u200a-\u200ayou will probably be deploying your first API in around ten minutes.\n\nI'm not joking, it's super easy. Let's get started.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/how-to-deploy-a-flask-api-8d54dd8d8b8a\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free article link:\nTO ADD", "Category": "Science & Technology", "Like Count": 75.0, "Dislike Count": 2.0}
{"Video ID": "NNS5pOpjvAQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "All You Need to Know on Multilingual Sentence Vectors (1 Model, 50+ Languages)", "Time Created": "2021-11-04 11:27:18 UTC", "Time Published": "2021-11-04 13:00:10 UTC", "Duration": "2392 seconds", "Description": "We\u2019ve learned about how sentence transformers can be used to create high-quality vector representations of text. We can then use these vectors to find similar vectors, which can be used for many applications such as semantic search or topic modeling.\n\nThese models are very good at producing meaningful, information-dense vectors. But they don\u2019t allow us to compare sentences across different languages.\n\nOften this may not be a problem. However, the world is becoming increasingly interconnected, and many companies span across multiple borders and languages. Naturally, there is a need for sentence vectors that are language agnostic.\n\nUnfortunately, very few textual similarity datasets span multiple languages, particularly for less common languages. And the standard training methods used for sentence transformers would require these types of datasets.\n\nDifferent approaches need to be used. Fortunately, some techniques allow us to extend models to other languages using more easily obtained language translations.\n\nIn this video, we will cover how multilingual models work and are built. We\u2019ll learn how to develop our own multilingual sentence transformers, the datasets to look for, and how to use high-performing pretrained multilingual models.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/multilingual-transformers/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:19 Multilingual Vectors\n05:55 Multi-task Training (mUSE)\n09:36 Multilingual Knowledge Distillation\n11:13 Knowledge Distillation Training\n13:43 Visual Walkthrough\n14:53 Parallel Data Prep\n20:23 Choosing a Student Model\n24:55 Initializing the Models\n30:05 ParallelSentencesDataset\n33:54 Loss and Fine-tuning\n36:59 Model Evaluation\n39:23 Outro", "Category": "Science & Technology", "Like Count": 30.0, "Dislike Count": 0.0}
{"Video ID": " -td57YvJdHc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Question-Answering in NLP (Extractive QA and Abstractive QA)", "Time Created": "2021-11-13 19:09:02 UTC", "Time Published": "2021-11-16 12:06:13 UTC", "Duration": "2886 seconds", "Description": "Search is a crucial functionality in many applications and companies globally. Whether in manufacturing, finance, healthcare, or *almost* any other industry, organizations have vast internal information and document repositories.\n\nUnfortunately, the scale of many companies\u2019 data means that the organization and accessibility of information can become incredibly inefficient. The problem is exacerbated for language-based information. Language is a tool for people to communicate often abstract ideas and concepts. Naturally, ideas and concepts are harder for a computer to comprehend and store in a meaningful way.\n\nHow do we minimize this problem? The answer lies with *semantic search*, specifically with the question-answering (QA) flavor of semantic search.\n\nThis article will introduce the different forms of QA, the components of these 'QA stacks', and where we might use them.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/question-answering/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Meaningful Search\n01:23 Use-case\n02:22 Open Domain QA (ODQA)\n06:41 SQuAD Format\n10:45 Quick Preprocessing\n15:18 Creating Context Vectors Database\n23:24 Open-book Extractive QA\n32:50 Open-book Abstractive QA\n41:53 Closed-book Abstractive QA\n47:27 Final Thoughts", "Category": "Science & Technology", "Like Count": 72.0, "Dislike Count": 0.0}
{"Video ID": "pNvujJ1XyeQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Today Unsupervised Sentence Transformers, Tomorrow Skynet (how TSDAE works)", "Time Created": "2021-11-24 14:20:20 UTC", "Time Published": "2021-11-24 16:24:24 UTC", "Duration": "2661 seconds", "Description": "To adapt a pretrained transformer to produce meaningful sentence vectors, we typically need a more supervised fine-tuning approach. We can use datasets like natural language inference (NLI) pairs, labeled semantic textual similarity (STS) data, or parallel data (pairs of translations).\n\nFor some domains and languages, such as finance and English, this data is fairly easy to find or gather. But many domains and many languages have very little labeled data. If you can find semantic similarity pairs for the agriculture industry, please let me know. There are many languages, such as Dhivehi, where unlabelled data is hard to find and labelled data practically non-existent.\n\nThis means you either spend a very long time gathering tens of thousands of labeled samples or you can try an unsupervised fine-tuning approach.\n\nUnsupervised training methods for sentence transformers are not as effective as their supervised counterparts, but they do work. And if you have no other choice, why not?\n\nIn this video, we will introduce the concept of unsupervised fine-tuning for sentence transformers. We will learn to train these models using the unsupervised Transformer-based Sequential Denoising Auto-Encoder (TSDAE) approach.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/unsupervised-training-sentence-transformers/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Why Language Embedding Matters\n05:12 Supervised Methods\n05:29 Natural Language Inference\n07:15 Semantic Textual Similarity\n07:43 Multilingual Training\n10:00 TSDAE (Unsupervised)\n18:50 Data Preparation\n29:05 Initialize Model\n32:39 Model Training\n36:25 NLTK Error\n37:15 Evaluation\n41:01 TSDAE vs Supervised Methods\n42:42 Why TSDAE is Cool", "Category": "Science & Technology", "Like Count": 70.0, "Dislike Count": 0.0}
{"Video ID": "3IPCEeh4xTg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Making The Most of Data: Augmented SBERT", "Time Created": "2021-12-16 15:46:03 UTC", "Time Published": "2021-12-17 14:24:40 UTC", "Duration": "3310 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nML models are data-hungry. They consume massive amounts of data to identify generalized patterns and apply those learned patterns to new data.\n\nAs models get bigger, so do datasets. And although we have seen an explosion of data in the past decade, it is often not accessible or in an ML-friendly format, especially in niche domains.\n\nFor many niche, low-resource domains, finding or annotating a substantial dataset manually is practically impossible.\n\nFortunately, we don't need to label (or even find) this new data. Instead, we can automatically generate or label data using one or more *data augmentation* techniques.\n\nIn this video, we will introduce data augmentation and its application to the field of NLP. We will focus on the 'in-domain' flavor of a particular data-augmentation strategy named augmented SBERT (AugSBERT).\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/data-augmentation/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 42.0, "Dislike Count": 0.0}
{"Video ID": "mjKqP3kRxbQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building Transformer Tokenizers (Dhivehi NLP #1)", "Time Created": "2021-12-28 15:02:22 UTC", "Time Published": "2021-12-28 15:45:03 UTC", "Duration": "1982 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nGet in touch with Ashraq:\nhttps://www.linkedin.com/in/ismailashraq/\n\nThe language of Dhivehi (or Maldivian) is fascinating. It uses a complex writing system known as Thaana, and I absolutely cannot comprehend any of it. It is so wildly different from anything I know\u200a-\u200abut, like the archipelago, it looks wonderful.\n\nAshraq described the difficulty of applying NLP to his native tongue of Dhivehi. There are several reasons for this, which we will explore in this video, and learn how to build an effective Dhivehi WordPiece tokenizer.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/designing-tokenizers-for-low-resource-languages-7faa4ab30ef4\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Article Friend Link (Free Access):\nhttps://towardsdatascience.com/designing-tokenizers-for-low-resource-languages-7faa4ab30ef4?sk=c0c16de9eea7dbe1d2a9c106abf38e1a\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:06 Dhivehi Project\n02:28 Hurdles for Low Resource Domains\n04:21 Dhivehi Dataset\n04:52 Download Dhivehi Corpus\n08:25 Tokenizer Components\n08:44 Normalizer Component\n11:55 Pre-tokenization Component\n14:59 Post-tokenization Component\n16:26 Decoder Component\n17:41 Tokenizer Implementation\n21:04 Tokenizer Training\n24:22 Post-processing Implementation\n27:12 Decoder Implementation\n28:07 Saving for Transformers\n30:33 Tokenizer Test and Usage\n31:36 Download Dhivehi Models\n32:21 First Steps", "Category": "Science & Technology", "Like Count": 49.0, "Dislike Count": 0.0}
{"Video ID": "a8jyue22SJM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "AugSBERT: Domain Transfer for Sentence Transformers", "Time Created": "2022-01-04 05:14:16 UTC", "Time Published": "2022-01-04 14:59:50 UTC", "Duration": "1750 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nWhen building language models, we can spend months optimizing training and model parameters, but it\u2019s useless if we don't have the correct data.\n\nThe success of our language models relies first and foremost on data. The augmented SBERT training strategy can help us.\n\nGiven this scenario, we can transfer information from an out-of-domain (or *source*) dataset to our target domain. We will learn how to do this here. First, we will learn to assess which source datasets align best with our target domain quickly. Then we will explain and work through the AugSBERT domain-transfer training strategy.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/augsbert-domain-transfer/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd17 n-gram Similarity Script: https://gist.github.com/jamescalam/b73f37017ae32bd6094747c4b0fca94a\n\ud83d\udd17 AugSBERT In-Domain Article: https://www.pinecone.io/learn/data-augmentation/\n\n00:00 Why Use Domain Transfer\n04:08 Strategy Outline\n06:05 Train Source Cross-Encoder\n12:44 Cross-Encoder Outcome\n15:12 Labeling Target Data\n20:31 Training Bi-encoder\n23:58 Evaluator Bi-encoder Performance\n28:08 Final Points", "Category": "Science & Technology", "Like Count": 41.0, "Dislike Count": 0.0}
{"Video ID": "w1dMEWm7jBc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build a Q&A AI in Python (Open-domain Question-Answering)", "Time Created": "2022-01-10 07:19:13 UTC", "Time Published": "2022-01-11 14:00:20 UTC", "Duration": "2364 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHow can we design these natural, human-like Q&A interfaces? The answer is open-domain question-answering (ODQA). ODQA allows us to use natural language to query a database.\n\nThat means that, given a dataset like a set of internal company documents, online documentation, or as is the case with Google, everything on the world\u2019s internet, we can retrieve relevant information in a natural, more human way.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/retriever-models/\n\n\ud83d\udd17 Nils YT Talk: https://youtu.be/XNJThigyvos?t=118\n\ud83d\udd17 MNR Loss Article: \n\ud83d\udd17 Free Pinecone API Key: https://app.pinecone.io/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Why QA\n04:05 Open Domain QA\n08:24 Do we need to fine-tune?\n11:44 How Retriever Training Works\n12:59 SQuAD Training Data\n16:29 Retriever Fine-tuning\n19:32 IR Evaluation\n25:58 Vector Database Setup\n33:42 Querying\n37:41 Final Notes", "Category": "Science & Technology", "Like Count": 66.0, "Dislike Count": 1.0}
{"Video ID": " -fzCSPsfMic", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build a Q&A Reader Model in Python (Open-domain QA)", "Time Created": "2022-01-18 12:17:09 UTC", "Time Published": "2022-01-18 16:37:37 UTC", "Duration": "1504 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nOpen-domain question-answering (ODQA) is a wildly popular *pipeline* of databases and language models that allow us to ask a machine human-like questions and return comprehensible and even intelligent answers.\n\nDespite the outward guise of simplicity, ODQA requires a reasonably advanced set of components placed together to enable the *extractive* Q&A functionality.\n\nWe call this *extractive* Q&A because the models are not generating an answer. Instead, the answer already exists but is hidden somewhere within potentially thousands, millions, or even more data sources.\n\nBy enabling extractive Q&A, we enable a more *intelligent* and *efficient* way to retrieve information from what can be massive stores of data.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/reader-models/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:13 ODQA Components\n03:09 Data Preprocessing\n22:35 Fine-tuning", "Category": "Science & Technology", "Like Count": 26.0, "Dislike Count": 0.0}
{"Video ID": "JLKUV-LiXjk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #1 - Installation and API", "Time Created": "2022-01-25 12:04:00 UTC", "Time Published": "2022-01-25 16:00:09 UTC", "Duration": "735 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 2:\nhttps://www.youtube.com/watch?v=U0EoaFFGyTg&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=2\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:39 App Outline\n03:36 Streamlit Installation\n06:15 Streamlit API Basics", "Category": "Science & Technology", "Like Count": 32.0, "Dislike Count": 0.0}
{"Video ID": "U0EoaFFGyTg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #2 - ML Models and APIs", "Time Created": "2022-01-26 16:07:51 UTC", "Time Published": "2022-01-26 16:30:36 UTC", "Duration": "911 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 3:\nhttps://www.youtube.com/watch?v=lYDiSCDcxmc&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=3\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\ud83d\udd17 Code to Create Index:\nhttps://gist.github.com/jamescalam/2123ce0bb8a871f48a151a023a7ece67\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:47 Creating the Vector DB\n08:56 Implementing Retrieval", "Category": "Science & Technology", "Like Count": 19.0, "Dislike Count": 0.0}
{"Video ID": "lYDiSCDcxmc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #3 - Make Apps Fast with Caching", "Time Created": "2022-01-27 13:13:14 UTC", "Time Published": "2022-01-27 15:00:36 UTC", "Duration": "584 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 4:\nhttps://www.youtube.com/watch?v=XdxeKiY2UXg&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=4\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:35 Streamlit Caching\n06:56 Experimental Caching Primitives", "Category": "Science & Technology", "Like Count": 24.0, "Dislike Count": 0.0}
{"Video ID": "XdxeKiY2UXg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #4 - Adding Bootstrap Components", "Time Created": "2022-01-28 10:05:43 UTC", "Time Published": "2022-01-28 15:11:42 UTC", "Duration": "590 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.1:\nhttps://www.youtube.com/watch?v=SGazDb8o-to&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=5\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:35 Streamlit Caching\n06:56 Experimental Caching Primitives", "Category": "Science & Technology", "Like Count": 38.0, "Dislike Count": 1.0}
{"Video ID": "JydpRavoJqI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Adding New Doc Stores to Haystack", "Time Created": "2022-02-15 04:56:36 UTC", "Time Published": "2022-03-15 15:00:14 UTC", "Duration": "1825 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:15 Contributing or Testing\n03:31 ODQA\n06:20 What is Haystack?\n08:13 Haystack QA Workflow\n14:52 Contributing to Open Source\n22:54 Haystack Doc Stores\n26:09 Doc Store Core Methods\n29:31 Final Notes, Contribute/Test", "Category": "Science & Technology", "Like Count": 14.0, "Dislike Count": 0.0}
{"Video ID": "SGazDb8o-to", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.1 - Custom React Components in Streamlit Setup", "Time Created": "2022-02-17 15:24:47 UTC", "Time Published": "2022-02-17 15:45:58 UTC", "Duration": "1158 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.2:\nhttps://www.youtube.com/watch?v=mxm8ihWoVbk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=6\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:19 Environment Setup\n03:42 Starting with a Template\n07:41 Naming for Card Component\n11:31 Installing Node Packages\n15:12 Running the Component", "Category": "Science & Technology", "Like Count": 26.0, "Dislike Count": 1.0}
{"Video ID": "mxm8ihWoVbk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.2 - MUI Card Component Build", "Time Created": "2022-02-20 15:25:56 UTC", "Time Published": "2022-02-21 14:00:31 UTC", "Duration": "1619 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.3:\nhttps://www.youtube.com/watch?v=lZ2EaPUnV7k&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=7\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:59 Clearing Card Component\n04:59 Building the Component\n14:22 Pulling in MUI Code\n24:08 Adding Roboto Font\n26:05 Final Points", "Category": "Science & Technology", "Like Count": 16.0, "Dislike Count": 1.0}
{"Video ID": "lZ2EaPUnV7k", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.3 - Publishing Components to Pip", "Time Created": "2022-02-27 16:28:49 UTC", "Time Published": "2022-02-28 17:00:29 UTC", "Duration": "858 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u2757 Python Packaging Video:\nhttps://youtu.be/JkeNVaiUq_c\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:09 PyPI\n02:41 Preparing for Distribution\n05:43 Build React Component\n06:39 Create Python Package\n11:57 Pip Install\n13:58 Ending", "Category": "Science & Technology", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "J0cntjLKpmU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Train Sentence Transformers by Generating Queries (GenQ)", "Time Created": "2022-03-08 03:10:28 UTC", "Time Published": "2022-03-08 14:52:23 UTC", "Duration": "1634 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nFine-tuning effective dense retrieval models is challenging. Bi-encoders (sentence transformers) are the current best models for dense retrieval in semantic search. Unfortunately, they're also notoriously data-hungry models that typically require a particular type of labeled training data.\n\nHard problems like this attract attention. As expected, there is plenty of attention on building ever better techniques for training retrievers.\n\nOne of the most impressive is GenQ. This approach to building bi-encoder retrievers uses the latest text generation techniques to synthetically generate training data. In short, all we need are passages of text. The generation model then augments these passages with synthetic queries, giving us the exact format we need to train an effective bi-encoder model.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/genq/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:32 Why GenQ?\n02:23 GenQ Overview\n04:28 Training Data\n06:48 Asymmetric Semantic Search\n07:54 T5 Query Generation\n13:52 Finetuning Bi-encoders\n16:02 GenQ Code Walkthrough\n21:40 Finetuning Bi-encoder Walkthrough\n26:48 Final Points", "Category": "Science & Technology", "Like Count": 39.0, "Dislike Count": 0.0}
{"Video ID": "Dn8OYkatiU0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Testing the New Haystack Doc Store", "Time Created": "2022-03-22 17:15:10 UTC", "Time Published": "2022-03-22 19:26:00 UTC", "Duration": "1399 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:19 Demo Start and Install\n03:25 Initialization\n06:30 Download and Write Documents\n10:55 Extractive QA Pipeline\n11:23 Fetch by ID\n19:01 Metadata Filtering\n22:24 Get All Documents", "Category": "Science & Technology", "Like Count": 5.0, "Dislike Count": 0.0}
{"Video ID": "uEbCXwInnPs", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Is GPL the Future of Sentence Transformers? | Generative Pseudo-Labeling Deep Dive", "Time Created": "2022-03-29 10:46:39 UTC", "Time Published": "2022-03-30 12:52:39 UTC", "Duration": "3175 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nTraining sentence transformers is hard; they need vast amounts of labeled data. On one hand, the internet is full of data, and, on the other, this data is *not* in the format we need. We usually need to use a supervised training method to train a high-performance bi-encoder (sentence transformer) model.\n\nThere is research producing techniques placing us ever closer to fine-tuning high-perfomance bi-encoder models with unlabeled text data. One of the most promising is GPL. At its core, GPL allows us to take unstructured text data and use it to build models that can understand this text. These models can then intelligently respond to natural language queries regarding this same text data.\n\nIt is a fascinating approach, with massive potential across innumerous use cases spanning all industries and borders. With that in mind, let's dive into the details of GPL and how we can implement it to build high-performance LMs with nothing more than plain text.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/gpl/\n\n\ud83d\udd17 Notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/nlp_course/gpl\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:08 Semantic Web and Other Uses\n04:36 Why GPL?\n07:31 How GPL Works\n10:37 Query Generation\n12:08 CORD-19 Dataset and Download\n13:27 Query Generation Code\n21:53 Query Generation is Not Perfect\n22:39 Negative Mining\n26:28 Negative Mining Implementation\n27:21 Negative Mining Code\n35:19 Pseudo-Labeling\n35:55 Pseudo-Labeling Code\n37:01 Importance of Pseudo-Labeling\n41:20 Margin MSE Loss\n43:40 MarginMSE Fine-tune Code\n46:30 Choosing Number of Steps\n48:54 Fast Evaluation\n51:43 What's Next for Sentence Transformers?", "Category": "Science & Technology", "Like Count": 76.0, "Dislike Count": 2.0}
{"Video ID": "j3psNM5y-eA", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Implementing Filters in the New Haystack Doc Store", "Time Created": "2022-04-06 15:53:46 UTC", "Time Published": "2022-04-06 16:26:54 UTC", "Duration": "1695 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nJoin me as I work through the final few PR issues on the latest Haystack document store, and figure out how Haystack's filter_utils work.\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:41 Filtering\n05:36 Testing Existing Filter Utils\n07:57 Making Sense of Filter Utils\n10:35 Writing the First Filter\n16:26 First Working Filter\n18:24 Testing New Filters\n21:27 Implementing in the Doc Store\n24:02 Testing Pipeline Filters\n27:11 Final Issue and Outro", "Category": "Science & Technology", "Like Count": 3.0, "Dislike Count": 0.0}
{"Video ID": "ok0SDdXdat8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Spotify's Podcast Search Explained", "Time Created": "2022-04-13 15:02:31 UTC", "Time Published": "2022-04-14 13:14:50 UTC", "Duration": "2998 seconds", "Description": "The market for podcasts has grown tremendously in recent years.\n\nDriving the charge in podcast adoption is Spotify. In a few short years, they have become the undisputed leaders in podcasting. Despite only entering the game in 2018, by late 2021, Spotify had already usurped Apple, the long-reigning leader in podcasts, with more than 28M monthly podcast listeners.\n\nTo back their podcast investments, Spotify has worked on making the podcast experience as seamless and accessible as possible. From their all-in-one podcast creation app (Anchor) to podcast APIs and their latest natural language enabled podcast search.\n\nSpotify\u2019s natural language search for podcasts is a fascinating use case. In the past, users had to rely on keyword/term matching to find the podcast episodes they wanted. Now, they can search in natural language, in much the same way we might ask a real person where to find something.\n\nIn this video, we will take a look under the hood of Spotify's podcast search, and learn how to implement a similar system ourselves.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/spotify-podcast-search\n\n\ud83d\udd17 Code and tests:\nhttps://github.com/pinecone-io/examples/tree/spotify-podcast-search/learn/search-in-wild/spotify-podcast-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:16 NLP in Semantic Search\n08:35 Why Now?\n09:29 Transformer Models\n11:52 Sentence Transformers\n13:12 Vector Search\n15:56 How Spotify Built Podcast Search\n17:35 Data Source, Fine-tuning, and Eval\n22:58 Code Implementation, Dataset\n24:44 Data Preparation\n26:39 Query Generation\n29:54 Fine-tuning a Podcast Model\n41:40 Evaluation\n48:05 Does it Scale?\n49:00 Sharing Your Work", "Category": "Science & Technology", "Like Count": 58.0, "Dislike Count": 1.0}
{"Video ID": "gVAJ_l_S7uQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to learn NLP for free", "Time Created": "2022-04-24 16:41:28 UTC", "Time Published": "2022-04-26 13:05:48 UTC", "Duration": "1402 seconds", "Description": "Knowing what to learn is one of the hardest parts about self-learning. Imagine being thrown into the wilderness and being told to find a specific landmark. Without a map you will end up wandering to wilderness with no better option than taking one step after another.\n\nI spent a long time wandering step-by-step and eventually found my way into working with deep learning and NLP full-time.\n\nHere I will share many of the resources I used or wish I had used in the past. You can this \"curriculum\" as a rough guideline in self-learning ML and working towards a full-time position.\n\nALL LINKS in article/friend link below:\n\n\ud83d\udcd5 Medium article:\nhttps://jamescalam.medium.com/the-self-taught-nlp-engineer-curriculum-c425c3fc3ff6\n\n\ud83d\udcd6 Friend link:\nhttps://jamescalam.medium.com/the-self-taught-nlp-engineer-curriculum-c425c3fc3ff6?sk=986263c644d9b36699d800713faa478a\n\n---\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:53 ML 101 + Prerequisites\n04:58 Sentdex + Neural Nets from Scratch\n07:32 ML Coursera\n09:31 100 Page ML Book\n11:14 Applied ML + Daniel Bourke\n13:17 Origin of Modern NLP\n13:41 CS224N\n14:44 NLP Specialization Coursera\n15:57 Modern NLP + Transformers Intro\n16:54 Transformer Courses\n18:14 Doing Projects\n19:18 Semantic + Vector Search\n19:54 NLP for Semantic Search\n20:44 Mining of Massive Datasets\n22:27 Final Points", "Category": "Science & Technology", "Like Count": 165.0, "Dislike Count": 1.0}
{"Video ID": "fb7LENb9eag", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "BERTopic Explained", "Time Created": "2022-05-10 14:13:06 UTC", "Time Published": "2022-05-11 15:10:23 UTC", "Duration": "2714 seconds", "Description": "90% of the world's data is unstructured. It is built by humans, for humans. That's great for human consumption, but it is *very* hard to organize when we begin dealing with the massive amounts of data abundant in today's information age.\n\nOrganization is complicated because unstructured text data is not intended to be understood by machines, and having humans process this abundance of data is wildly expensive and *very slow*.\n\nFortunately, there is light at the end of the tunnel. More and more of this unstructured text is becoming accessible and understood by machines. We can now search text based on *meaning*, identify the sentiment of text, extract entities, and much more.\n\nTransformers are behind much of this. These transformers are (unfortunately) not Michael Bay's Autobots and Decepticons and (fortunately) not buzzing electrical boxes. Our NLP transformers lie somewhere in the middle, they're not sentient Autobots (yet), but they can understand language in a way that existed only in sci-fi until a short few years ago.\n\nMachines with a human-like comprehension of language are pretty helpful for organizing masses of unstructured text data. In machine learning, we refer to this task as *topic modeling*, the automatic clustering of data into particular topics.\n\nBERTopic takes advantage of the superior language capabilities of these (not yet sentient) transformer models and uses some other ML magic like UMAP and HDBSCAN (more on these later) to produce what is one of the most advanced techniques in language topic modeling today.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/bertopic\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/algos-and-libraries/bertopic\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:40 In this video\n02:58 BERTopic Getting Started\n08:48 BERTopic Components\n15:21 Transformer Embedding\n18:33 Dimensionality Reduction\n25:07 UMAP\n31:48 Clustering\n37:22 c-TF-IDF\n40:49 Custom BERTopic\n44:04 Final Thoughts", "Category": "Science & Technology", "Like Count": 153.0, "Dislike Count": 3.0}
{"Video ID": "O9lrWt15wH8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Long Form Question Answering (LFQA) in Haystack", "Time Created": "2022-05-17 15:22:17 UTC", "Time Published": "2022-05-17 15:46:21 UTC", "Duration": "2159 seconds", "Description": "Question-Answering (QA) has exploded as a subdomain of Natural Language Processing (NLP) in the last few years. QA is a widely applicable use case in NLP yet was out of reach until the introduction of [transformer models](/learn/transformers/) in 2017.\n\nWithout transformer models, the level of language comprehension required to make something as complex as QA work simply was not possible.\n\nAlthough QA is a complex topic, it comes from a simple idea. The automatic retrieval of information via a more human-like interaction. The task of information retrieval (IR) is performed by almost every organization in the world. Without other options, organizations rely on person-to-person IR and rigid keyword search tools. This haphazard approach to IR generates a lot of friction, particularly for larger organizations.\n\nQA offers a solution to this problem. Rather than these documents being lost in an abyss, they can be stored within a space where an intelligent QA agent can access them. Unlike humans, our QA agent can scan millions of documents in seconds and return answers from these documents almost instantly.\n\nWith QA tools, employees can stop wasting time searching for snippets of information and focus on their *real*, value-adding tasks.\n\nA small investment in QA is, for most organizations, a no-brainer.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/haystack-lfqa\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/blob/master/integrations/haystack/haystack_lfqa.ipynb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:20 Approaches to Question Answering\n05:43 Components of QA Pipeline\n08:58 LFQA Generator\n09:40 Haystack Setup\n10:32 Initialize Document Store\n13:02 Getting Data\n17:53 Indexing Embeddings\n21:51 Initialize Generator\n24:10 Asking Questions\n26:12 Common Problems\n29:32 Generator Memory\n31:30 Few More Questions\n34:54 Outro", "Category": "Science & Technology", "Like Count": 55.0, "Dislike Count": 1.0}
{"Video ID": "uYas6ysyjgY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "New GPU-Acceleration for PyTorch on M1 Macs! + using with BERT", "Time Created": "2022-05-22 16:37:37 UTC", "Time Published": "2022-05-24 13:00:34 UTC", "Duration": "1140 seconds", "Description": "GPU-acceleration on Mac is finally here!\n\nToday's deep learning models owe a great deal of their exponential performance gains to ever increasing model sizes. Those larger models require more computations to train and run.\n\nThese models are simply too big to be run on CPU hardware, which performs large step-by-step computations. Instead, they need massively parallel computations. That leaves us with either GPU or TPU hardware.\n\nOur home PCs aren't coming with TPUs anytime soon, so we're left with the GPU option. GPUs use a highly parallel structure, originally designed to process images for visual heavy processes. They became essential components in gaming for rendering real-time 3D images.\n\nGPUs are essential for the scale of today's models. Using CPUs makes many of these models too slow to be useful, which can make deep learning on M1 machines rather disappointing.\n\nFortunately, this is changing with the support of GPU on M1 machines beginning with PyTorch v1.12. In this video we will explain the new integration and how to implement it yourself.\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/gpu-acceleration-comes-to-pytorch-on-m1-macs-195c399efcc1\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/gpu-acceleration-comes-to-pytorch-on-m1-macs-195c399efcc1?sk=a88acd35f600858093c177b97d690b03\n\n\ud83d\udd17  Code notebooks:\nhttps://github.com/jamescalam/pytorch-mps\n\n\ud83e\udd16  70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89  Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e  Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:34 PyTorch MPS\n04:57 Installing ARM Python\n09:09 Using PyTorch with GPU\n12:14 BERT on PyTorch GPU\n13:51 Best way to train LLMs on Mac\n16:01 Buffer Size Bug\n17:24 When we would use Mac M1 GPU", "Category": "Science & Technology", "Like Count": 115.0, "Dislike Count": 3.0}
{"Video ID": "FzLIIwiaXSU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build an AI-Powered Video Search App", "Time Created": "2022-06-01 12:37:21 UTC", "Time Published": "2022-06-01 16:29:43 UTC", "Duration": "1343 seconds", "Description": "Technology and culture have advanced and become ever more entangled. Some of the most significant technological breakthroughs are integrated so tightly into our culture that we never even notice they\u2019re there.\n\nOne of those is AI-powered search. It powers your Google results, Netflix recommendations, and ads you see everywhere. It is being rapidly weaved throughout all aspects of our lives. Further, this is a new technology; its full potential is unknown.\n\nThis technology weaves directly into the cultural phenomenon of YouTube. Imagine a search engine like Google that allows you to rapidly access the billions of hours of YouTube content. There is no comparison to that level of highly engaging video content in the world.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/youtube-search\n\n\ud83d\udd17 Code:\nhttps://github.com/pinecone-io/examples/tree/master/learn/projects/yt-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:56 YouTube Search App\n04:43 Getting Data\n07:58 Enhancing the Data\n12:45 Scraping Other Metadata\n14:52 Loading Data from Hugging Face\n15:42 Index and Query the Data\n20:43 Streamlit App Code", "Category": "Science & Technology", "Like Count": 58.0, "Dislike Count": 0.0}
{"Video ID": "xXsDIK9z_fg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Using Semantic Search to Find GIFs", "Time Created": "2022-06-06 09:17:01 UTC", "Time Published": "2022-06-07 12:05:40 UTC", "Duration": "1050 seconds", "Description": "Vector search powers some of the most popular services in the world. It serves your Google results, delivers the best podcasts on Spotify, and accounts for at least 35% of consumer purchases on Amazon.\n\nIn this article, we will use vector search applied to language, called semantic search, to build a GIF search engine. Unlike more traditional search where we rely on keyword matching, semantic search enables search based on the human meaning behind text and images. That means we can find highly relevant GIFs with natural language prompts.\n\nThe pipeline for a project like this is simple, yet powerful. It can easily be adapted to tasks as diverse as video search or answering Super Bowl questions, or as we\u2019ll see, finding GIFs.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/gif-search\n\n\ud83d\udd17 Code:\nhttps://github.com/pinecone-io/examples/tree/master/learn/projects/gif-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:17 GIF Search Demo\n01:56 Pipeline Overview\n05:33 Data Preparation\n08:17 Vector Database and Retriever\n12:37 Querying\n15:42 Streamlit App Code", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 1.0}
{"Video ID": "_OAU1kQdmgE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Learn Data Science | ML | Programming", "Time Created": "2022-06-15 10:37:57 UTC", "Time Published": "2022-06-15 13:11:47 UTC", "Duration": "992 seconds", "Description": "In this video I share five of the approaches/thoughts I have regarding learning, in particular for learning data science, machine learning, or programming.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:33 Scale of Theory vs. Applied\n02:55 Shape of Learning\n05:52 Courses vs. Projects\n08:37 Open Source\n10:44 Writing\n12:44 Following Interests\n15:42 Final Notes", "Category": "Education", "Like Count": 24.0, "Dislike Count": 0.0}
{"Video ID": "BD9TkvEsKwM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Evaluation Measures for Search and Recommender Systems", "Time Created": "2022-06-25 14:35:27 UTC", "Time Published": "2022-06-28 15:06:40 UTC", "Duration": "1885 seconds", "Description": "In this video you will learn about popular offline metrics (evaluation measures) like Recall@K, Mean Reciprocal Rank (MRR), Mean Average Precision@K (MAP@K), and Normalized Discounted Cumulative Gain (NDCG@K). We will also demonstrate how each of these metrics can be replicated in Python.\n\nEvaluation of information retrieval (IR) systems is critical to making well-informed design decisions. From search to recommendations, evaluation measures are paramount to understanding what does and does not work in retrieval.\n\nMany big tech companies contribute much of their success to well-built IR systems. One of Amazon\u2019s earliest iterations of the technology was reportedly driving more than 35% of their sales. Google attributes 70% of YouTube views to their IR recommender systems.\n\nIR systems power some of the greatest companies in the world, and behind every successful IR system is a set of evaluation measures.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/offline-evaluation\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/algos-and-libraries/offline-evaluation\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:51 Offline Metrics\n02:38 Dataset and Retrieval 101\n06:08 Recall@K\n07:57 Recall@K in Python\n09:03 Disadvantages of Recall@K\n10:21 MRR\n13:32 MRR in Python\n14:18 MAP@K\n18:17 MAP@K in Python\n19:27 NDCG@K\n29:26 Pros and Cons of NDCG@K\n29:48 Final Thoughts", "Category": "Science & Technology", "Like Count": 49.0, "Dislike Count": 0.0}
{"Video ID": "coaaSxys5so", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build next-level Q&A with OpenAI", "Time Created": "2022-07-06 19:48:54 UTC", "Time Published": "2022-07-07 13:24:35 UTC", "Duration": "1168 seconds", "Description": "Walkthrough of the OpenAI x Pinecone Q&A app I built for a webinar with OpenAI. This is the coolest Q&A app I've ever built thanks to Pinecone vector search and OpenAI's incredible embeddings and generation endpoints.\n\nLINKS:\n\ud83d\udd79 App:\nhttps://pinecone-io-playground-beyond-search-openaisrcserver-h65vzl.streamlitapp.com\n\ud83d\udc68\u200d\ud83d\udcbb Code and Data:\nhttps://github.com/pinecone-io/examples/tree/master/integrations/openai/beyond_search_webinar\nOpenAI x Pinecone Webinar:\n\u25b6\ufe0f https://www.youtube.com/watch?v=HtI9easWtAA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 36.0, "Dislike Count": 0.0}
{"Video ID": "I3na13AESjw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to use Color Histograms for Image Retrieval", "Time Created": "2022-07-11 07:01:31 UTC", "Time Published": "2022-07-13 16:22:08 UTC", "Duration": "1864 seconds", "Description": "Browsing, searching, and retrieving images has never been easy. Traditionally, many technologies relied on manually appending metadata to images and searching via this metadata. This approach works for datasets with high-quality annotation, but most datasets are too large for manual annotation.\n\nThat means any large image dataset must rely on Content-Based Image Retrieval (CBIR). Search with CBIR focuses on comparing the *content* of an image rather than its metadata. Content can be color, shapes, textures \u2013 or with some of the latest advances in ML \u2014 the \"human meaning\" behind an image.\n\nColor histograms represent one of the first CBIR techniques, allowing us to search through images based on their color profiles rather than metadata.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/color-histograms\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:23 What are Color Histograms?\n08:39 How to Built Color Histograms\n16:56 Using OpenCV calcHist\n20:36 Image Retrieval\n27:37 Pros and Cons\n30:40 Final Points", "Category": "Science & Technology", "Like Count": 23.0, "Dislike Count": 0.0}
{"Video ID": "UzkdOg7wWmI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "\ud83e\udd17 Hugging Face just released *Diffusers* - for models like DALL-E 2 and Imagen!", "Time Created": "2022-07-23 21:33:08 UTC", "Time Published": "2022-07-26 15:27:46 UTC", "Duration": "934 seconds", "Description": "Hugging Face of transformer fame have created a whole new Python library for diffusion models! Diffusion models are a key component of models like OpenAI's DALL-E-2, Google's Imagen, and Midjourney's image generation service. HuggingFace Diffusers brings these models to a new level of accessibility (and open source!).\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/hugging-face-just-released-the-diffusers-library-846f32845e65\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/hugging-face-just-released-the-diffusers-library-846f32845e65?sk=9ec4027460defa1fd25178af9a55da13\n\n\ud83e\udde8 Diffusers:\nhttps://github.com/huggingface/diffusers\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n00:00 What are Diffusers?\n01:55 Getting started\n04:20 Prompt engineering\n09:34 Testing other diffusers", "Category": "Science & Technology", "Like Count": 61.0, "Dislike Count": 0.0}
{"Video ID": "szfG55juoJE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How I work from anywhere", "Time Created": "2022-07-24 14:01:51 UTC", "Time Published": "2022-08-16 13:55:16 UTC", "Duration": "767 seconds", "Description": "Overview of how I deal with travel and work. Remote desk setup for staying as ergonomic and productive as possible, enjoy!\n\n\ud83d\udd17 Links to products (mostly affiliate):\nLaptop stand: https://amzn.to/3bZqMHM\nSecond screen: https://amzn.to/3w6IT5B\nCable bag (international): https://amzn.to/3QBH7S7\n                              ... or UK: https://amzn.to/3ps5lT2\nPeak Design backpacks: https://www.peakdesign.com/products/everyday-backpack\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 32.0, "Dislike Count": 1.0}
{"Video ID": "jjQetJtQDS4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Bag of *Visual* Words for Image Classification and Retrieval", "Time Created": "2022-08-02 20:39:30 UTC", "Time Published": "2022-08-03 13:00:35 UTC", "Duration": "3367 seconds", "Description": "In computer vision, bag of visual words (BoVW) is one of the pre-deep learning models used for building image embeddings. Allowing us to retrieve images from a database that are similar to another \"query\" image, perform object detection, and image classification.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/bag-of-visual-words/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 33.0, "Dislike Count": 0.0}
{"Video ID": "989aKUVBfbk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fast intro to multi-modal ML with OpenAI's CLIP", "Time Created": "2022-08-11 06:17:14 UTC", "Time Published": "2022-08-11 13:03:08 UTC", "Duration": "1374 seconds", "Description": "OpenAI's CLIP is \"multi-modal\" model capable of understanding the relationships and concepts between both text and images. As we'll see, CLIP is very capable, and when used via the Hugging Face library, could not be easier to work with.\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/quick-fire-guide-to-multi-modal-ml-with-openais-clip-2dad7e398ac0\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/quick-fire-guide-to-multi-modal-ml-with-openais-clip-2dad7e398ac0?sk=89bb2d8b8e583ed109d8a05e00366645\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:15 What is CLIP?\n02:13 Getting started\n05:38 Creating text embeddings\n07:23 Creating image embeddings\n10:26 Embedding a lot of images\n15:08 Text-image similarity search\n21:38 Alternative image and text search", "Category": "Science & Technology", "Like Count": 31.0, "Dislike Count": 0.0}
{"Video ID": "c_u4AHNjOpk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "AlexNet and ImageNet Explained", "Time Created": "2022-08-23 22:13:25 UTC", "Time Published": "2022-08-24 13:00:22 UTC", "Duration": "2180 seconds", "Description": "Today\u2019s deep learning revolution traces back to the 30th of September, 2012. On this day, a Convolutional Neural Network (CNN) called AlexNet won the ImageNet 2012 challenge. AlexNet didn\u2019t just win; it dominated.\n\nAlexNet was unlike the other competitors. This new model demonstrated unparalleled performance on the largest image dataset of the time, ImageNet. This event made AlexNet the first widely acknowledged, successful application of deep learning. It caught people\u2019s attention with a 9.8 percentage point advantage over the nearest competitor.\n\nUntil this point, deep learning was a nice idea that most deemed as impractical. AlexNet showed that deep learning was more than a pipedream, and the authors showed the world how to make it practical. Yet, the surge of deep learning that followed was not fueled solely by AlexNet. Indeed, without the huge ImageNet dataset, there would have been no AlexNet.\n\nThe future of AI was to be built on the foundations set by the ImageNet challenge and the novel solutions that enabled the synergy between ImageNet and AlexNet.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/imagenet\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:06 Birth of Deep Learning\n02:52 ImageNet\n07:56 Lack of Readiness for Big Datasets\n09:57 ImageNet Challenge (ILSVRC)\n11:47 AlexNet\n19:30 PYTORCH IMPLEMENTATION\n19:55 Data Preprocessing\n27:06 Class Prediction with AlexNet\n31:50 Goldfish Results\n34:27 Closing Notes", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "pfwBut7E60Q", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Ultra-efficient Classifier Fine-tuning with Vector Search", "Time Created": "2022-08-31 00:32:14 UTC", "Time Published": "2022-08-31 13:00:26 UTC", "Duration": "1932 seconds", "Description": "Learn how to use vector search to create highly targeted training for any classification model using a final linear classification layer. Easily fine-tune models in 10 minutes with less than 100 labeled examples.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/classifier-train-vector-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:14 Classification\n02:49 Better Classifier Training\n06:33 Classification as Vector Search\n08:47 How Fine-tuning Works\n10:50 Identifying Important Samples\n12:39 CODE IMPLEMENTATION\n13:13 Indexing\n18:59 Fine-tuning the Classifier\n27:37 Classifier Predictions\n30:43 Closing Notes", "Category": "Science & Technology", "Like Count": 49.0, "Dislike Count": 0.0}
{"Video ID": " -S20nblUuNw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hugging Face Datasets #1 - Hosting your datasets", "Time Created": "2022-09-09 12:52:32 UTC", "Time Published": "2022-09-09 14:18:34 UTC", "Duration": "1382 seconds", "Description": "Introduction to Hugging Face datasets, how it works, and how to host your own simple datasets (JSONL, TSV, CSV, etc) for free via Hugging Face Datasets Hub\n\nWarp download:\nhttps://app.warp.dev/referral/7G3N39\n\nGit LFS Install:\nMac:\n$ brew install git-lfs\nDebian/Ubuntu:\n$ curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash\n$ sudo apt-get install git-lfs\nWindows:\nGet install from https://github.com/git-lfs/git-lfs/releases\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:36 Creating our own Datasets\n08:29 Creating JSONL for Hugging Face\n15:15 Uploading Datasets for Git\n19:10 LFS for Large Files\n21:56 Closing Notes", "Category": "Science & Technology", "Like Count": 14.0, "Dislike Count": 0.0}
{"Video ID": "fGwH2YoQkDM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "CLIP Explained | Multi-modal ML", "Time Created": "2022-09-14 23:08:40 UTC", "Time Published": "2022-09-15 13:00:22 UTC", "Duration": "2013 seconds", "Description": "Language models (LMs) can not rely on language alone. That is the idea behind the \"Experience Grounds Language\" paper, that proposes a framework to measure LMs' current and future progress. A key idea is that, beyond a certain threshold LMs need other forms of data, such as visual input.\n\nThe next step beyond well-known language models; BERT, GPT-3, and T5 is \u201dWorld Scope 3\u201d. In World Scope 3, we move from large text-only datasets to large multi-modal datasets. That is, datasets containing information from multiple forms of media, like *both* images and text.\n\nThe world, both digital and real, is multi-modal. We perceive the world as an orchestra of language, imagery, video, smell, touch, and more. This chaotic ensemble produces an inner state, our \"model\" of the outside world.\n\nAI must move in the same direction. Even specialist models that focus on language or vision must, at some point, have input from the other modalities. How can a model fully understand the concept of the word \"person\" without *seeing* a person?\n\nOpenAI's Contrastive Learning In Pretraining (CLIP) is a world scope three model. It can comprehend concepts in both text and image and even connect concepts between the two modalities. In this video we will learn about multi-modality, how CLIP works, and how to use CLIP for different use cases like encoding, classification, and object detection.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/clip/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 50.0, "Dislike Count": 1.0}
{"Video ID": "ODdKC30dT8c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hugging Face Datasets #2 - Dataset Builder Scripts", "Time Created": "2022-09-23 14:06:51 UTC", "Time Published": "2022-09-23 14:45:22 UTC", "Duration": "1404 seconds", "Description": "How to work with dataset builder scripts, intro to the download manager, and Apache Arrow datatypes used in Hugging Face Datasets.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:49 Creating Compressed Files\n02:41 Creating Dataset Build Script\n04:49 Download Manager\n08:59 Finishing Split Generator\n10:13 Generate Examples Method\n14:47 Add Dataset to Hugging Face\n17:49 Apache Arrow Features\n22:52 What's Next?", "Category": "Science & Technology", "Like Count": 14.0, "Dislike Count": 0.0}
{"Video ID": "98POYg2HZqQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Zero-Shot Image Classification with OpenAI's CLIP", "Time Created": "2022-10-04 05:29:02 UTC", "Time Published": "2022-10-05 14:00:03 UTC", "Duration": "1303 seconds", "Description": "State-of-the-art (SotA) computer vision (CV) models are characterized by a *restricted* understanding of the visual world specific to their training data [1].\n\nThese models can perform *very well* on specific tasks and datasets, but they do not generalize well. They cannot handle new classes or images beyond the domain they have been trained with.\n\nIdeally, a CV model should learn the contents of images without excessive focus on the specific labels it is initially trained to understand.\n\nFortunately, OpenAI's CLIP has proved itself as an incredibly flexible CV classification model that often requires *zero* retraining. In this chapter, we will explore CLIP in zero-shot image classification.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/clip-classification/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 12.0, "Dislike Count": 0.0}
{"Video ID": "Jk1YP4Y_U_0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Stoic Philosophy Text Generation with TensorFlow", "Time Created": "2020-04-19 11:33:45 UTC", "Time Published": "2020-04-19 13:52:43 UTC", "Duration": "1859 seconds", "Description": "Explanation of key parts to a RNN text generator built in TensorFlow with Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nI've written a couple of Medium articles on this project, if you're interested check them out here:\nStoic Philosophy - Built by Algorithms\nhttps://towardsdatascience.com/stoic-philosophy-built-by-algorithms-9cff7b91dcbd\nSupercharged Prediction with Ensemble Learning\nhttps://towardsdatascience.com/recurrent-ensemble-learning-caffdcd94092\n\nMusic used by Lakey Inspired.\n1 - Blue Boi\n2 - Falling\nhttps://www.youtube.com/channel/UCOmy8wuTpC95lefU5d1dt2Q", "Category": "People & Blogs", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "gXqHd6-NKBo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build TensorFlow Pipelines with tf.data.Dataset", "Time Created": "2020-11-02 08:23:38 UTC", "Time Published": "2020-11-02 08:57:48 UTC", "Duration": "1853 seconds", "Description": "Link to updated version (without video freeze): https://youtu.be/f6XVfgJTbp4\n\nAn introduction to building better input pipelines for Machine Learning in TF2.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to tf.data API docs: https://www.tensorflow.org/guide/data", "Category": "People & Blogs", "Like Count": 46.0, "Dislike Count": 9.0}
{"Video ID": "yYEPNla4tlQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Every New Feature in Python 3.10.0a2", "Time Created": "2020-11-08 18:09:49 UTC", "Time Published": "2020-11-10 16:44:05 UTC", "Duration": "883 seconds", "Description": "Every new feature in the early release alpha 2 preview of Python 3.10\n\nThere is video lag 5:00 - 9:55 covering the Type Alias section (sorry!) - the audio is okay though\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "People & Blogs", "Like Count": 88.0, "Dislike Count": 5.0}
{"Video ID": "GYDFBfx8Ts8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Build a Transformer for Language Classification in TensorFlow", "Time Created": "2020-11-19 09:57:27 UTC", "Time Published": "2020-11-19 12:20:35 UTC", "Duration": "2299 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHow to build a transformer model for sentiment analysis (language classification) using HuggingFace's Transformers library in TensorFlow 2 with Python.\n\nWe cover the full process from downloading data all the way through to building and training the transformer model.\n\nThis is a multi-class classification problem using both TensorFlow and Transformers to build a multiclass sentiment classifier.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nArticle version is here:\nhttps://betterprogramming.pub/build-a-natural-language-classifier-with-bert-and-tensorflow-4770d4442d41\n\nOr here (free link if you don't have Medium membership):\nhttps://betterprogramming.pub/build-a-natural-language-classifier-with-bert-and-tensorflow-4770d4442d41?sk=346cd4ce5ee019c400835588b56d8574\n\nArticle extract:\n\"High-performance transformer models like BERT and GPT-3 are transforming a huge array of previously menial, language-based tasks, into the work of a few clicks, saving a lot of time.\n\nIn most industries, the newest wave of language optimization is just getting started \u2014 taking their first baby steps. But these seedlings are widespread, and sprouting quickly.\n\nMuch of this adoption is thanks to the incredibly low barrier-to-entry. If you know the basics of TensorFlow or PyTorch, and take a little time to get to grips with the Transformers library \u2014 you\u2019re already halfway there.\n\nWith the Transformers library, it takes just three lines of code to initialize a cutting-edge ML model \u2014 a model built from the billions of research dollars spent by the likes of Google, Facebook, and OpenAI.\n\nThis article will take you through the steps to build a classification model that leverages the power of transformers, using Google\u2019s BERT.\n\nTransformers\n- Finding Models\n- Initializing\n- Bert Inputs and Outputs\nClassification\n- The Data\n- Tokenization\n- Data Prep\n- Train-Validation Split\n- Model Definition\n- Train\"", "Category": "People & Blogs", "Like Count": 384.0, "Dislike Count": 12.0}
{"Video ID": "DgGFhQmfxHo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to use the Kaggle API in Python", "Time Created": "2020-11-22 20:19:30 UTC", "Time Published": "2020-11-22 20:29:27 UTC", "Duration": "462 seconds", "Description": "Simple step-by-step tutorial covering the setup and use of the Kaggle API for downloading datasets using the Kaggle library in Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "People & Blogs", "Like Count": 121.0, "Dislike Count": 6.0}
{"Video ID": "YvVQgvAz9dY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Language Generation with OpenAI's GPT-2 in Python", "Time Created": "2020-11-23 12:36:44 UTC", "Time Published": "2020-11-24 14:22:46 UTC", "Duration": "498 seconds", "Description": "Easy natural language generation with Transformers and PyTorch. We apply OpenAI's GPT-2 model to generate text in just a few lines of Python code.\n\nLanguage generation is one of those natural language tasks that can really produce an incredible feeling of awe at how far the fields of machine learning and artificial intelligence have come.\n\nGPT-1, 2, and 3 are OpenAI\u2019s top language models \u2014 well known for their ability to produce incredibly natural, coherent, and genuinely interesting language.\n\nIn this article, we will take a small snippet of text and learn how to feed that into a pre-trained GPT-2 model using PyTorch and Transformers to produce high-quality language generation in just eight lines of code. We cover:\n\nPyTorch and Transformers\n- Data\nBuilding the Model\n- Initialization\n- Tokenization\n- Generation\n- Decoding\nResults\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium Article:\nhttps://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b\n\nFriend Link (free access):\nhttps://towardsdatascience.com/text-generation-with-python-and-gpt-2-1fecbff1635b?sk=930367d835f15abb4ef3164f7791e1b1\n\nThumbnail background by gustavo centurion on Unsplash\nhttps://unsplash.com/photos/O6fs4ablxw8", "Category": "People & Blogs", "Like Count": 133.0, "Dislike Count": 1.0}
{"Video ID": "egDIqQIjDCI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Text Summarization with Google AI's T5 in Python", "Time Created": "2020-11-24 21:26:27 UTC", "Time Published": "2020-11-27 06:00:07 UTC", "Duration": "419 seconds", "Description": "Easy text summarization using Google AI's T5 model using HuggingFace transformers and PyTorch in Python.\n\nAutomatic text summarization allows us to shorten long pieces of text into easy-to-read, short snippets that still convey the most important and relevant information of the original text.\n\nIn this video, we\u2019ll build a simple but incredibly powerful text summarizer using Google\u2019s T5. We\u2019ll be using the PyTorch and HuggingFace\u2019s Transformers frameworks.\n\nThis is split into three parts:\n1. Import and Initialization\n2. Data and Tokenization\n3. Summary Generation\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nYou can read the article version of this on Medium here:\nhttps://betterprogramming.pub/how-to-summarize-text-with-googles-t5-4dd1ae6238b6\n\n(And for those of you without Medium membership, here's a free link):\nhttps://betterprogramming.pub/how-to-summarize-text-with-googles-t5-4dd1ae6238b6?sk=740d3009282cb2c4f7478a0c073dedb3\n\nThumbnail background by gustavo centurion on Unsplash\nhttps://unsplash.com/photos/O6fs4ablxw8", "Category": "People & Blogs", "Like Count": 115.0, "Dislike Count": 1.0}
{"Video ID": "DFtP1THE8fE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to do Sentiment Analysis with Flair in Python", "Time Created": "2020-12-04 11:15:10 UTC", "Time Published": "2020-12-04 14:00:03 UTC", "Duration": "848 seconds", "Description": "Learn how to perform powerful sentiment analysis with no fine-tuning or pre-training required using the Flair NLP library in Python.\n\nWith the real-time information available to us on massive social media platforms like Twitter, we have all the data we could ever need to create these accurate and up-to-date sentiment metrics for different companies.\n\nBut then comes the question, how can our computer understand what this unstructured text data means?\n\nThat is where sentiment analysis comes in. Sentiment analysis is a particularly interesting branch of Natural Language Processing (NLP), which is used to rate the language used in a body of text.\n\nThrough sentiment analysis, we can take thousands of tweets about a company and judge whether they are generally positive or negative (the sentiment) in real-time!\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/sentiment-analysis-for-stock-price-prediction-in-python-bed40c65d178\n\n(Free link if you don't have Medium membership):\nhttps://towardsdatascience.com/sentiment-analysis-for-stock-price-prediction-in-python-bed40c65d178?sk=1cbf33a5d1fd2ed841f9487972c1cbed\n\nThumbnail photo by Alexander London on Unsplash\nhttps://unsplash.com/@alxndr_london", "Category": "People & Blogs", "Like Count": 64.0, "Dislike Count": 2.0}
{"Video ID": "8o3jvkK2GGU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Python Environment Setup for Machine Learning", "Time Created": "2020-12-23 13:50:07 UTC", "Time Published": "2020-12-23 13:53:02 UTC", "Duration": "754 seconds", "Description": "Everything you need for a Python environment set up for Machine Learning and Data Science!\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/how-to-setup-python-for-machine-learning-173cb25f0206\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Christian Wiediger on Unsplash\nhttps://unsplash.com/@christianw", "Category": "People & Blogs", "Like Count": 38.0, "Dislike Count": 1.0}
{"Video ID": "BYbJ_HH788U", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Functional API - TensorFlow Essentials #2", "Time Created": "2020-12-28 16:41:11 UTC", "Time Published": "2020-12-29 10:04:40 UTC", "Duration": "341 seconds", "Description": "A look at the functional API method for building models in TensorFlow 2 for Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Darius Bashar on Unsplash\nhttps://unsplash.com/@dariusbashar?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "_8Bydxud1XU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training Parameters - TensorFlow Essentials #3", "Time Created": "2020-12-28 19:30:23 UTC", "Time Published": "2020-12-29 23:37:57 UTC", "Duration": "450 seconds", "Description": "Learn how to set up model training parameters and compile the model before training.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Alex McCarthy on Unsplash\nhttps://unsplash.com/@4lexmccarthy?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 17.0, "Dislike Count": 0.0}
{"Video ID": "f6XVfgJTbp4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Input Data Pipelines - TensorFlow Essentials #4", "Time Created": "2020-12-28 23:25:54 UTC", "Time Published": "2020-12-30 11:30:02 UTC", "Duration": "751 seconds", "Description": "Learn how to set-up efficient and clean input data pipelines using tf.data.Dataset\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nThumbnail background by Daria Nepriakhina on Unsplash\nhttps://unsplash.com/@epicantus?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 54.0, "Dislike Count": 0.0}
{"Video ID": "MQD1yMnZ_jk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sequential Model - TensorFlow Essentials #1", "Time Created": "2020-12-29 09:46:00 UTC", "Time Published": "2020-12-29 09:50:23 UTC", "Duration": "391 seconds", "Description": "Learn how to use the sequential model building approach in TensorFlow 2.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nBackground thumbnail by Aryan Dhiman on Unsplash\nhttps://unsplash.com/@mylifeasaryan_?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText", "Category": "Education", "Like Count": 84.0, "Dislike Count": 1.0}
{"Video ID": "KTFWNI0qL28", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "6 of Python's Newest and Best Features (3.7-3.9)", "Time Created": "2021-01-12 23:31:26 UTC", "Time Published": "2021-01-12 23:58:12 UTC", "Duration": "1084 seconds", "Description": "A rundown of the six most recent, and coolest features added to Python in the past few years!\n\n2018 brought us a plethora of new features with the release of Python 3.7, followed by 3.8 in 2019, and 3.9 in 2020.\n\nMany of those changes were behind the scenes. Optimizations and upgrades that the vast majority of us will never notice, despite their benefits.\n\nOthers are more obvious, additions to syntax or functionality that can change how we write our code. But even these visible changes can be hard to keep up with.\n\nIn this video, we will run through the more apparent upgrades to provide a brief but hopefully invaluable refresher on everything new to Python from the past few years.\n\n- Python 3.7\n  - Breakpoints\n- Python 3.8\n  - Walrus Operator\n  - F-string '=' Specifier\n  - Positional-only Parameters\n- Python 3.9\n  - More Type Hinting\n  - Dictionary Unions\n\nMedium Article:\nhttps://towardsdatascience.com/amazing-features-added-to-python-from-3-7-to-now-4f35f0bb1ea6\n\n(Free access link):\nhttps://towardsdatascience.com/amazing-features-added-to-python-from-3-7-to-now-4f35f0bb1ea6?sk=bda3cb7717caa969b81619f85191f241\n\nThumbnail background by Martin Sanchez on Unsplash:\nhttps://unsplash.com/photos/4PDPLw1flgE\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 15.0, "Dislike Count": 2.0}
{"Video ID": "GyJtxd14DTc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Novice to Advanced RegEx in Less-than 30 Minutes + Python", "Time Created": "2021-01-27 09:06:42 UTC", "Time Published": "2021-01-27 09:51:32 UTC", "Duration": "1769 seconds", "Description": "A full tutorial covering everything you need to know about Regular Expressions - an essential for anyone learning to code - and even more so for anyone interested in Natural Language Processing.\n\nThis video includes:\n\n- metacharacters\n- quantifiers\n- capture groups\n- using capture groups in Python\n- character sets\n- look-ahead and look-behind assertions\n- negative look-ahead and look-behind assertions\n- inline modifiers\n- passing modifiers as function parameters in Python\n- conditionals (if-else statements for RegEx)\n- re.match\n- re.search\n- re.findall\n\nWe cover all of this in-depth in this tutorial, incl. examples all the way through on RegEx101 (an interactive debugging/regex building tool) and also in Python.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 239.0, "Dislike Count": 8.0}
{"Video ID": "1ZcXmjZtJJ8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building a PlotLy $GME Chart in Python", "Time Created": "2021-02-02 13:38:16 UTC", "Time Published": "2021-02-07 13:24:45 UTC", "Duration": "4492 seconds", "Description": "A code-along video covering the coding process from imagination to Python.\nSomething a little different, I'm not overly keen on this format - it's pretty long - but I've recorded it and I think maybe this can be useful for a few of you.\nI haven't prepared anything beforehand, this is just going into the coding process with a rough outline of wanting to build a stock chart for GME (GameStop) and adding a few technical indicators - to get more familiar with PlotLy and the AlphaVantage API.\nSo, it's a weird one, but I hope a few of you enjoy it - thanks :)\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "ZIRmXkHp0-c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Custom Q&A Transformer Models in Python", "Time Created": "2021-02-09 20:42:56 UTC", "Time Published": "2021-02-12 13:30:03 UTC", "Duration": "4216 seconds", "Description": "In this video, we will learn how to take a pre-trained transformer model and train it for question-and-answering. We will be using the HuggingFace transformers library with the PyTorch implementation of models in Python.\n\nTransformers are one of the biggest developments in Natural Language Processing (NLP) and learning how to use them properly is basically a data science superpower - they're genuinely amazing I promise!\n\nI hope you enjoy the video :)\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/the-ultimate-performance-metric-in-nlp-111df6c64460\n\n(Free link):\nhttps://towardsdatascience.com/how-to-fine-tune-a-q-a-transformer-86f91ec92997?sk=9344fd51afe71a0905db833d0183d436\n\nCode:\nhttps://gist.github.com/jamescalam/55daf50c8da9eb3a7c18de058bc139a3\n\nPhoto in thumbnail by Lorenzo Herrera on Unsplash\nhttps://unsplash.com/@lorenzoherrera", "Category": "Education", "Like Count": 163.0, "Dislike Count": 5.0}
{"Video ID": "FdjVoOf9HN4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Use The Reddit API in Python", "Time Created": "2021-02-12 11:36:48 UTC", "Time Published": "2021-02-12 12:02:48 UTC", "Duration": "1401 seconds", "Description": "Learn how to use the Reddit API in Python, including setup, authorization, and pulling data from subreddits.\n\nReddit API docs:\nhttps://www.reddit.com/dev/api/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-use-the-reddit-api-in-python-5e05ddfd1e5c\n\n\ud83d\udcd6 Free link:\nhttps://towardsdatascience.com/how-to-use-the-reddit-api-in-python-5e05ddfd1e5c?sk=0295f297c1365bee7cc7a32bdff21b61\n\nExtract from article:\n\n\"Reddit is a huge ecosystem brimming with data that is readily available at our very fingertips. As a data-minded person, I wanted to take advantage of this and perform some analysis using this vast repository of open-source data.\nInitially, it turned out that getting to grip with Reddit\u2019s API wasn\u2019t as clear-cut as expected \u2014 despite being a straightforward process; it can be a little confusing at first.\nSo, after figuring everything out, I wrote this article \u2014 which I hope will help a few of you to get familiar with using the Reddit API in Python. We will cover:\nGetting Access\nMaking Requests\n  - Reading the Data\n  - Streaming New Posts\nParameters\n\nGetting Access\nFirst, we need access. Unlike most popular services, the Reddit API was somewhat difficult to figure out initially. There are several steps:\n1. Go to App Preferences and click create another app\u2026 at the bottom.\n2. Fill out the required details, make sure to select script \u2014 and click create app.\n3. make a note of the personal use script and secret tokens.\n4. Request a temporary OAuth token from Reddit. We need our username and password for this.\n5. Add headers=headers to every request. The OAuth token will expire after ~2 hours, and a new one will need to be requested.\n\"\n\nAnd so on, check it out if you're interested in reading (rather than watching).\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 627.0, "Dislike Count": 11.0}
{"Video ID": "scJsty_DR3o", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Q&A Models in Python (Transformers)", "Time Created": "2021-02-17 21:03:29 UTC", "Time Published": "2021-02-19 15:00:21 UTC", "Duration": "1189 seconds", "Description": "In this video we'll cover how to build a question-answering model in Python using HuggingFace's Transformers.\n\nYou will need to install the transformers library with:\npip install transformers\n\nAlongside either TensorFlow or PyTorch (to follow this video exactly you will need PyTorch). To install TensorFlow just type:\npip install tensorflow\nOR\nconda install tensorflow\n\nAnd for PyTorch follow the instructions under 'Install PyTorch' here:\nhttps://pytorch.org/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to Q&A fine-tuning video:\nhttps://youtu.be/ZIRmXkHp0-c\n\nYou can find the Medium article link below here:\nhttps://towardsdatascience.com/question-and-answering-with-bert-6ef89a78dac", "Category": "Education", "Like Count": 151.0, "Dislike Count": 1.0}
{"Video ID": "QJq9RTp_OVE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Decode Outputs From NLP Models (Python)", "Time Created": "2021-02-21 18:02:42 UTC", "Time Published": "2021-02-24 15:00:10 UTC", "Duration": "577 seconds", "Description": "In this video, we will cover three ways to decode the output probabilities from NLP models - greedy search, random sampling, and beam search.\n\nLearning how to decode outputs can make a huge difference in diagnosing model issues and improving text output quality - and as an added bonus it's super easy.\n\nOne of the often-overlooked parts of sequence generation in natural language processing (NLP) is how we select our output tokens \u2014 otherwise known as decoding.\n\nYou may be thinking \u2014 we select a token/word/character based on the probability of each token assigned by our model.\n\nThis is half-true \u2014 in language-based tasks, we typically build a model which outputs a set of probabilities to an array where each value in that array represents the probability of a specific word/token.\n\nAt this point, it might seem logical to select the token with the highest probability? Well, not really \u2014 this can create some unforeseen consequences \u2014 as we will see soon.\n\nWhen we are selecting a token in machine-generated text, we have a few alternative methods for performing this decode \u2014 and options for modifying the exact behavior too.\n\nIn this video we will explore three different methods for selecting our output token, these are:\n\n- Greedy Decoding\n- Random Sampling\n- Beam Search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nLink to the article version on Medium:\nhttps://towardsdatascience.com/the-three-decoding-methods-for-nlp-23ca59cb1e9d\n\nFree link (if you don't have membership):\nhttps://towardsdatascience.com/the-three-decoding-methods-for-nlp-23ca59cb1e9d?sk=64fbb0204c174dc520af027a69f88030", "Category": "Education", "Like Count": 28.0, "Dislike Count": 0.0}
{"Video ID": "TCZgXFPNnbc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Identify Stocks on Reddit with SpaCy (NER in Python)", "Time Created": "2021-03-01 21:47:29 UTC", "Time Published": "2021-03-03 14:27:48 UTC", "Duration": "1307 seconds", "Description": "We will learn how to process unstructured text data from Reddit and extract organization names so that any further analysis is automatically classified and results assigned to the correct stocks.\n\nOrganizations are mentioned in each subreddit in a variety of formats. Typically we will find two formats:\n\n- Organization name, eg Tesla/Tesla Motors\n- Ticker symbol, eg TSLA, tsla, or $TSLA\n\nWe also need to be able to differentiate between tickers and other abbreviations/slang -some of these are unclear like AI (AI can mean both artificial intelligence and refer to the ticker symbol for C3.ai).\n\nSo, we need a reasonable competent NER process to accurately classify our data.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nReddit API video: https://youtu.be/FdjVoOf9HN4\n/r/investing data: https://github.com/jamescalam/transformers/blob/main/course/named_entity_recognition/data/reddit_investing.csv\nMedium article: https://towardsdatascience.com/ner-for-extracting-stock-mentions-on-reddit-aa604e577be\n(Free version if you don't have Medium membership): https://towardsdatascience.com/ner-for-extracting-stock-mentions-on-reddit-aa604e577be?sk=d16305d40b18e7955a0665633182d2b4\n\nThanks for watching!", "Category": "Education", "Like Count": 33.0, "Dislike Count": 0.0}
{"Video ID": "yDGo9z_RlnE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentiment Analysis on ANY Length of Text With Transformers (Python)", "Time Created": "2021-03-10 08:15:21 UTC", "Time Published": "2021-03-10 13:15:03 UTC", "Duration": "1630 seconds", "Description": "The de-facto standard in many natural language processing (NLP) tasks nowadays is to use a transformer. Text generation? Transformer. Question-and-answering? Transformer. Language classification? Transformer!\n\nHowever, one of the problems with many of these models (a problem that is not just restricted to transformer models)  is that we cannot process long pieces of text.\n\nAlmost every article I write on Medium contains 1000+ words, which, when tokenized for a transformer model like BERT, will produce 1000+ tokens. BERT (and many other transformer models) will consume 512 tokens max\u200a-\u200atruncating anything beyond this length.\n\nAlthough I think you may struggle to find value in processing my Medium articles, the same applies to many useful data sources\u200a-\u200alike news articles or Reddit posts.\n\nWe will take a look at how we can work around this limitation. In this article, we will find the sentiment for long posts from the /r/investing subreddit. This video will cover:\n\nHigh-Level Approach\nGetting Started\n- Data\n- Initialization\nTokenization\nPreparing The Chunks\n- Split\n- CLS and SEP\n- Padding\n- Reshaping For BERT\nMaking Predictions\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nHere's a link to the Medium article:\nhttps://towardsdatascience.com/how-to-apply-transformers-to-any-length-of-text-a5601410af7f\n\nAnd a free access link if you don't have Medium membership:\nhttps://towardsdatascience.com/how-to-apply-transformers-to-any-length-of-text-a5601410af7f?sk=d4e717eb2ff31fb27ea67019bbb63ad6", "Category": "Education", "Like Count": 111.0, "Dislike Count": 2.0}
{"Video ID": "9Od9-DV9kd8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Unicode Normalization for NLP in Python", "Time Created": "2021-03-16 09:27:24 UTC", "Time Published": "2021-03-17 13:30:00 UTC", "Duration": "927 seconds", "Description": "\u2115\ud835\udd60-\ud835\udd60\ud835\udd5f\ud835\udd56 \ud835\udd5a\ud835\udd5f \ud835\udd65\ud835\udd59\ud835\udd56\ud835\udd5a\ud835\udd63 \ud835\udd63\ud835\udd5a\ud835\udd58\ud835\udd59\ud835\udd65 \ud835\udd5e\ud835\udd5a\ud835\udd5f\ud835\udd55 \ud835\udd68\ud835\udd60\ud835\udd66\ud835\udd5d\ud835\udd55 \ud835\udd56\ud835\udd67\ud835\udd56\ud835\udd63 \ud835\udd66\ud835\udd64\ud835\udd56 \ud835\udd65\ud835\udd59\ud835\udd56\ud835\udd64\ud835\udd56 \ud835\udd52\ud835\udd5f\ud835\udd5f\ud835\udd60\ud835\udd6a\ud835\udd5a\ud835\udd5f\ud835\udd58 \ud835\udd57\ud835\udd60\ud835\udd5f\ud835\udd65 \ud835\udd67\ud835\udd52\ud835\udd63\ud835\udd5a\ud835\udd52\ud835\udd5f\ud835\udd65\ud835\udd64. \ud835\udd4b\ud835\udd59\ud835\udd56 \ud835\udd68\ud835\udd60\ud835\udd63\ud835\udd64\ud835\udd65 \ud835\udd65\ud835\udd59\ud835\udd5a\ud835\udd5f\ud835\udd58, \ud835\udd5a\ud835\udd64 \ud835\udd5a\ud835\udd57 \ud835\udd6a\ud835\udd60\ud835\udd66 \ud835\udd55\ud835\udd60 \ud835\udd52\ud835\udd5f\ud835\udd6a \ud835\udd57\ud835\udd60\ud835\udd63\ud835\udd5e \ud835\udd60\ud835\udd57 \u2115\ud835\udd43\u2119 \ud835\udd52\ud835\udd5f\ud835\udd55 \ud835\udd6a\ud835\udd60\ud835\udd66 \ud835\udd59\ud835\udd52\ud835\udd67\ud835\udd56 \ud835\udd54\ud835\udd59\ud835\udd52\ud835\udd63\ud835\udd52\ud835\udd54\ud835\udd65\ud835\udd56\ud835\udd63\ud835\udd64 \ud835\udd5d\ud835\udd5a\ud835\udd5c\ud835\udd56 \ud835\udd65\ud835\udd59\ud835\udd5a\ud835\udd64 \ud835\udd5a\ud835\udd5f \ud835\udd6a\ud835\udd60\ud835\udd66\ud835\udd63 \ud835\udd5a\ud835\udd5f\ud835\udd61\ud835\udd66\ud835\udd65, \ud835\udd6a\ud835\udd60\ud835\udd66\ud835\udd63 \ud835\udd65\ud835\udd56\ud835\udd69\ud835\udd65 \ud835\udd53\ud835\udd56\ud835\udd54\ud835\udd60\ud835\udd5e\ud835\udd56\ud835\udd64 \ud835\udd54\ud835\udd60\ud835\udd5e\ud835\udd61\ud835\udd5d\ud835\udd56\ud835\udd65\ud835\udd56\ud835\udd5d\ud835\udd6a \ud835\udd66\ud835\udd5f\ud835\udd63\ud835\udd56\ud835\udd52\ud835\udd55\ud835\udd52\ud835\udd53\ud835\udd5d\ud835\udd56.\n\nWe also find that text like this is incredibly common\u200a-\u200aparticularly on social media.\n\nAnother pain-point comes from diacritics (the little glyphs in \u00c7, \u00e9, \u00c5) that you'll find in almost every European language.\n\nThese characters have a hidden property that can trip up any NLP model\u200a-\u200atake a look at the Unicode for two versions of \u00c7:\n\nLatin capital letter C with cedilla: \\u00C7\n\nLatin capital letter C + combining cedilla: \\u0043\\u0327\n\nBoth are completely different, despite rendering as the same character.\n\nTo deal with all of these text variants we need to use Unicode normalization - which we will cover in this video.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/what-on-earth-is-unicode-normalization-56c005c55ad0\n\nFriend link (free access):\nhttps://towardsdatascience.com/what-on-earth-is-unicode-normalization-56c005c55ad0?sk=0cd19a9ad9f5d948b33179bab3c3b7cd", "Category": "Education", "Like Count": 43.0, "Dislike Count": 0.0}
{"Video ID": "2qJavL-VX9Y", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "The NEW Match-Case Statement in Python 3.10", "Time Created": "2021-03-17 20:37:52 UTC", "Time Published": "2021-03-19 16:00:03 UTC", "Duration": "1088 seconds", "Description": "Python 3.10 is beginning to fill-out with plenty of fascinating new features. One of those, in particular, caught my attention\u200a-\u200astructural pattern matching\u200a-\u200aor as most of us will know it, switch/case statements.\n\nSwitch-statements have been absent from Python despite being a common feature of most languages. Python is leapfrogging ahead of those languages by introducing the match-case statement as a switch-case v2.0.\n\nBack in 2006, PEP 3103 was raised, recommending the implementation of a switch-case statement. However, after a poll at PyCon 2007 received no support for the feature, the Python devs dropped it.\n\nFast-forward to 2020, and Guido van Rossum, the creator of Python, committed the first documentation showing the new match-statements, which have been named Structural Pattern Matching, as found in PEP 634.\n\nLet's take a look at how this new logic works.\n\nMedium Article:\nhttps://towardsdatascience.com/switch-case-statements-are-coming-to-python-d0caf7b2bfd3\n\nFriend Link (free access):\nhttps://towardsdatascience.com/switch-case-statements-are-coming-to-python-d0caf7b2bfd3?sk=363e0f7696502647e007f91910b4c817\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:58 Switch-Case\n02:37 Flow of Logic\n03:21 Second Example (Tuples)\n05:00 Final Example Setup\n11:30 Final Example If-Else Version\n15:22 Final Example Match-Case Version", "Category": "Education", "Like Count": 310.0, "Dislike Count": 11.0}
{"Video ID": "pjtnkCGElcE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Multi-Class Language Classification With BERT in TensorFlow", "Time Created": "2021-03-24 17:51:01 UTC", "Time Published": "2021-03-25 16:00:15 UTC", "Duration": "2604 seconds", "Description": "Chapters for each section of the video (preprocessing, model build, prediction) are in the video timeline.\n\nTransformers have been described as the fourth pillar of deep learning [1], alongside the three big neural net architectures of CNNs, RNNs, and MLPs.\n\nHowever, from the perspective of natural language processing\u200a-\u200atransformers are much more than that. Since their introduction in 2017, they've come to dominate a majority of NLP benchmarks\u200a-\u200aand continue to impress daily.\n\nWhat I'm saying is, transformers are damn cool. And with libraries like HuggingFace's transformers\u200a-\u200ait has become too easy to build incredible solutions with them.\n\nSo, what's not to love? Incredible performance paired with the ultimate ease-of-use.\n\nIn this video, we'll work through building a multi-class classification model using transformers\u200a-\u200afrom start-to-finish.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/multi-class-classification-with-transformers-6cf7b59a033a\n\nFree access:\nhttps://towardsdatascience.com/multi-class-classification-with-transformers-6cf7b59a033a?sk=544872025c2283c54cf4294814b8cae3\n\nLink to Kaggle video:\nhttps://youtu.be/DgGFhQmfxHo\n\n[1] Fourth Pillar of AI:\nhttps://ark-invest.com/articles/analyst-research/transformers-comprise-the-fourth-pillar-of-deep-learning/\n\n00:00 Intro\n01:21 Pulling Data\n01:47 Preprocessing\n14:33 Data Input Pipeline\n24:14 Defining Model\n33:29 Model Training\n35:36 Saving and Loading Models\n37:37 Making Predictions", "Category": "Education", "Like Count": 264.0, "Dislike Count": 1.0}
{"Video ID": "JkeNVaiUq_c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build Python Packages for Pip", "Time Created": "2021-04-02 14:51:14 UTC", "Time Published": "2021-04-02 15:19:32 UTC", "Duration": "1267 seconds", "Description": "The most powerful feature of Python is its community. Almost every use-case out there has a package built specifically for it.\n\nNeed to send mobile/email alerts? pip install knockknock \u200a- \u200aBuild ML apps? pip install streamlit \u200a- \u200aBored of your terminal? pip install colorama\u200a - \u200aIt's too easy!\n\nI know this is obvious, but those libraries didn't magically appear. For each package, there is a person, or many persons\u200a-\u200athat actively developed and deployed that package.\n\nEvery single one.\n\nAll 300K+ of them.\n\nThat is why Python is Python, the level of support is phenomenal\u200a-\u200amindblowing.\n\nIn this video, we will learn how to build our own packages. And add them to the Python Package Index (PyPI). Afterward, we will be able to install our packages using pip install!\n\nGitHub Repo:\nhttps://github.com/jamescalam/aesthetic_ascii\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium Article:\nhttps://towardsdatascience.com/how-to-package-your-python-code-df5a7739ab2e\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/how-to-package-your-python-code-df5a7739ab2e?sk=04d9f67c0654445bbcbbf6825f535900", "Category": "Education", "Like Count": 390.0, "Dislike Count": 11.0}
{"Video ID": "4Jmq28RQ3hU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Structure a Q&A ML App", "Time Created": "2021-04-09 15:02:44 UTC", "Time Published": "2021-04-09 15:22:50 UTC", "Duration": "585 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nI'm planning on doing something different, a series of videos where we work through the steps - from start-to-finish - of (attempting) to build a Q&A web app that answers our questions with Stoic answers.\n\nIn this video, I'm outlining the idea and describing the high-level setup that I think we'll need to put together. It should be cool!\n\nWe'll be using the Haystack framework for 'Q&A at scale', which using HuggingFace transformers under-the-hood, and the Elasticsearch document store.\n\nFind the repo here:\nhttps://github.com/jamescalam/aurelius\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 46.0, "Dislike Count": 0.0}
{"Video ID": "Vwq7Ucp9UCw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Index Q&A Data With Haystack and Elasticsearch", "Time Created": "2021-04-11 21:30:32 UTC", "Time Published": "2021-04-12 15:00:11 UTC", "Duration": "807 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe second video in 'Building a Stoic Q&A App' - here we're setting up Elasticsearch and Haystack to store the data (Meditations) ready for retrieval when we ask our app questions.\n\nFind the code here:\nhttps://github.com/jamescalam/aurelius/tree/main/code/labs\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 79.0, "Dislike Count": 3.0}
{"Video ID": "DBsxUSUhfRg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Q&A Document Retrieval With DPR", "Time Created": "2021-04-12 14:44:59 UTC", "Time Published": "2021-04-15 15:00:10 UTC", "Duration": "890 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe third video in building our Stoic Q&A app.\n\nIn open-domain question answering, we typically design a model architecture that contains a data source, retriever, and reader/generator.\n\nThe first of these components is typically a document store. The two most popular stores we use here are Elasticsearch and FAISS.\n\nNext up is our retriever \u2014 the topic of this video. The job of the retriever is to filter through our document store for relevant chunks of information (the documents) and pass them to the reader/generator model.\n\nDPR (dense passage retriever) is a dense vector retriever that is trained on question-context pairs. Encoding both accordingly - enabling super accurate similarity indexing.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nIf you're interested in learning more about DPR, I wrote about it on Medium here:\nhttps://towardsdatascience.com/how-to-create-an-answer-from-a-question-with-dpr-d76e29cc5d60\n\n(Free link):\nhttps://towardsdatascience.com/how-to-create-an-answer-from-a-question-with-dpr-d76e29cc5d60?sk=1bdd7c1bff80bf51410962691c690c69\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 57.0, "Dislike Count": 0.0}
{"Video ID": "QrzHImDEq_w", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Use Type Annotations in Python", "Time Created": "2021-04-23 21:44:38 UTC", "Time Published": "2021-04-27 14:53:25 UTC", "Duration": "907 seconds", "Description": "Type annotations\u200a-\u200aalso known as type signatures\u200a-\u200aare used to indicate the datatypes of variables and input/outputs of functions and methods.\n\nIn many languages, datatypes are explicitly stated. In these languages, if you don't declare your datatype\u200a-\u200athe code will not run.\n\nType annotations have a long and convoluted history with Python, going all the way back to the first release of Python 3 with the initial implementation of function annotations.\n\nType annotations in Python are not make-or-break like in other languages (like C). They're optional chunks of syntax that we can add to make our code more explicit.\n\nErroneous type annotations will do nothing more than highlight the incorrect annotation in our code editor\u200a-\u200ano errors are ever raised due to annotations.\n\nSo, if type annotations are not enforced, why use them?\n\nWell, as we touched upon already\u200a-\u200adeclaring types makes our code more explicit, and if done well, easier to read\u200a-\u200aboth for ourselves and others.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nRead the Medium article here:\nhttps://towardsdatascience.com/type-annotations-in-python-d90990b172dc\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/type-annotations-in-python-d90990b172dc?sk=29bc29ab5478a842363963b421781b47\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:55 Datatypes Example in C\n2:53 Static and Dynamic Typed Languages\n3:47 Type Annotations in Python\n4:25 How to Define Simple Types\n6:04 IDE Warnings\n8:20 More Complex Types\n9:53 dict[str, int]\n11.07 Multiple Types\n11:38 Union Operator (Py 3.9)\n12:34 Union Operator (Py 3.10)\n13:21 Optional Operator", "Category": "Education", "Like Count": 132.0, "Dislike Count": 3.0}
{"Video ID": "2tdLYIKPafc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Extractive Q&A With Haystack and FastAPI in Python", "Time Created": "2021-04-26 22:03:55 UTC", "Time Published": "2021-04-29 15:00:04 UTC", "Duration": "1058 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nIn this video we work through building an extractive Q&A stack using Haystack, and embedding it within a FastAPI instance in Python.\n\nWe use the BERT transformer for our reader model, alongside Elasticsearch and the BM25 retriever algorithm.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 71.0, "Dislike Count": 1.0}
{"Video ID": "jVPd7lEvjtg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentence Similarity With Transformers and PyTorch (Python)", "Time Created": "2021-05-04 15:25:17 UTC", "Time Published": "2021-05-05 15:00:20 UTC", "Duration": "1270 seconds", "Description": "Easy mode: https://youtu.be/Ey81KfQ3PQU\n\nAll we ever seem to talk about nowadays are BERT this, BERT that. I want to talk about something else, but BERT is just too good \u200a- \u200aso this video will be about BERT for sentence similarity.\n\nA big part of NLP relies on similarity in highly-dimensional spaces. Typically an NLP solution will take some text, process it to create a big vector/array representing said text\u200a-\u200athen perform several transformations.\n\nIt's highly-dimensional magic.\n\nSentence similarity is one of the clearest examples of how powerful highly-dimensional magic can be.\n\nThe logic is this:\n- Take a sentence, convert it into a vector.\n- Take many other sentences, and convert them into vectors.\n- Find sentences that have the smallest distance (Euclidean) or smallest angle (cosine similarity) between them\u200a-\u200amore on that here.\n- We now have a measure of semantic similarity between sentences\u200a-\u200aeasy!\n\nAt a high level, there's not much else to it. But of course, we want to understand what is happening in a little more detail and implement this in Python too.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1?sk=c0f2990b4660210b447e52d55bd0f4e5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:16 BERT Base Network\n1:11 Sentence Vectors and Similarity\n1:47 The Data and Model\n3:01 Two Approaches\n3:16 Tokenizing Sentences\n9:11 Creating last_hidden_state Tensor\n11:08 Creating Sentence Vectors\n17:53 Cosine Similarity", "Category": "Education", "Like Count": 233.0, "Dislike Count": 2.0}
{"Video ID": "Ey81KfQ3PQU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Sentence Similarity With Sentence-Transformers in Python", "Time Created": "2021-05-04 19:55:42 UTC", "Time Published": "2021-05-05 15:00:09 UTC", "Duration": "370 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHard mode: https://youtu.be/jVPd7lEvjtg\n\nAll we ever seem to talk about nowadays are BERT this, BERT that. I want to talk about something else, but BERT is just too good \u200a- \u200aso this video will be about BERT for sentence similarity.\n\nA big part of NLP relies on similarity in highly-dimensional spaces. Typically an NLP solution will take some text, process it to create a big vector/array representing said text\u200a-\u200athen perform several transformations.\n\nIt's highly-dimensional magic.\n\nSentence similarity is one of the clearest examples of how powerful highly-dimensional magic can be.\n\nThe logic is this:\n- Take a sentence, convert it into a vector.\n- Take many other sentences, and convert them into vectors.\n- Find sentences that have the smallest distance (Euclidean) or smallest angle (cosine similarity) between them\u200a-\u200amore on that here.\n- We now have a measure of semantic similarity between sentences\u200a-\u200aeasy!\n\nAt a high level, there's not much else to it. But of course, we want to understand what is happening in a little more detail and implement this in Python too.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-measuring-text-similarity-eec91c6bf9e1?sk=c0f2990b4660210b447e52d55bd0f4e5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 370.0, "Dislike Count": 4.0}
{"Video ID": "W8ZPQOcHnlE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "NER With Transformers and spaCy (Python)", "Time Created": "2021-05-09 20:57:10 UTC", "Time Published": "2021-05-11 15:00:28 UTC", "Duration": "567 seconds", "Description": "Named entity recognition (NER) consists of extracting 'entities' from text\u200a-\u200awhat we mean by that is given the sentence:\n\n\"Apple reached an all-time high stock price of 143 dollars this January.\"\n\nWe might want to extract the key pieces of information\u200a-\u200aor 'entities'\u200a-\u200aand categorize each of those entities. Like so:\n\n- Apple \u200a: Organization\n- 143 dollars\u200a: \u200aMonetary Value\n- this January\u200a: \u200aDate\n\nFor us humans, this is easy. But how can we teach a machine to distinguish between a granny smith apple and the Apple we trade on NASDAQ?\n\n(No, we can't rely on the 'A' being capitalized\u2026)\n\nThis is where NER comes in\u200a-\u200ausing NER, we can extract keywords like apple and identify that it is, in fact, an organization\u200a-\u200anot a fruit.\n\nThe go-to library for NER is spaCy, which is incredible. But what if we added transformers to spaCy? Even better - we'll cover exactly that in this video.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5", "Category": "Education", "Like Count": 120.0, "Dislike Count": 2.0}
{"Video ID": "q9NS5WpfkrU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #1 - Masked-Language Modeling (MLM)", "Time Created": "2021-05-19 09:31:26 UTC", "Time Published": "2021-05-19 14:51:39 UTC", "Duration": "984 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nBERT, everyone's favorite transformer costs Google ~$7K to train (and who knows how much in R&D costs). From there, we write a couple of lines of code to use the same model\u200a-\u200aall for free.\n\nBERT has enjoyed unparalleled success in NLP thanks to two unique training approaches, masked-language modeling (MLM), and next sentence prediction (NSP).\n\nMLM consists of giving BERT a sentence and optimizing the weights inside BERT to output the same sentence on the other side.\n\nSo we input a sentence and ask that BERT outputs the same sentence.\n\nHowever, before we actually give BERT that input sentence\u200a-\u200awe mask a few tokens.\n\nSo we're actually inputting an incomplete sentence and asking BERT to complete it for us.\n\nHow to train BERT with MLM:\nhttps://youtu.be/R6hcxMMOrPE\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\nMedium article:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c?sk=17a19eca8dc8280bea4138802580ffe0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://www.udemy.com/course/nlp-with-transformers/?couponCode=MEDIUM3\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 277.0, "Dislike Count": 3.0}
{"Video ID": "R6hcxMMOrPE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #2 - Train With Masked-Language Modeling (MLM)", "Time Created": "2021-05-19 11:38:10 UTC", "Time Published": "2021-05-19 14:51:49 UTC", "Duration": "1666 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nBERT has enjoyed unparalleled success in NLP thanks to two unique training approaches, masked-language modeling (MLM), and next sentence prediction (NSP).\n\nIn many cases, we might be able to take the pre-trained BERT model out-of-the-box and apply it successfully to our own language tasks.\n\nBut often, we might need to pre-train the model for a specific use case even further.\n\nFurther training with MLM allows us to tune BERT to better understand the particular use of language in a more specific domain.\n\nOut-of-the-box BERT\u200a-\u200agreat for general purpose use. Fine-tuned with MLM BERT\u200a-\u200agreat for domain-specific use.\n\nIn this video, we'll cover exactly how to fine-tune BERT models using MLM in PyTorch.\n\n\ud83d\udc7e Code:\nhttps://github.com/jamescalam/transformers/blob/main/course/training/03_mlm_training.ipynb\n\nMeditations data:\nhttps://github.com/jamescalam/transformers/blob/main/data/text/meditations/clean.txt\n\nUnderstanding MLM:\nhttps://youtu.be/q9NS5WpfkrU\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/masked-language-modelling-with-bert-7d49793e5d2c?sk=17a19eca8dc8280bea4138802580ffe0\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 223.0, "Dislike Count": 1.0}
{"Video ID": "1gN1snKBLP0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #3 - Next Sentence Prediction (NSP)", "Time Created": "2021-05-23 18:14:04 UTC", "Time Published": "2021-05-25 14:56:47 UTC", "Duration": "823 seconds", "Description": "Next sentence prediction (NSP) is one-half of the training process behind the BERT model (the other being masked-language modeling\u200a-\u200aMLM).\n\nWhere MLM teaches BERT to understand relationships between words\u200a-\u200aNSP teaches BERT to understand relationships between sentences.\n\nIn the original BERT paper, it was found that without NSP, BERT performed worse on every single metric - \u200aso it's important.\n\nNow, when we use a pre-trained BERT model, training with NSP and MLM has already been done, so why do we need to know about it?\n\nWell, we can actually further pre-train these pre-trained BERT models so that they better understand the language used in our specific use-cases. To do that, we can use both MLM and NSP.\n\nSo, in this video, we'll go into depth on what NSP is, how it works, and how we can implement it in code.\n\nTraining with NSP:\nhttps://youtu.be/x1lAcT3xl5M\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f?sk=3595968413abde1c5833e1a96e449673\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 94.0, "Dislike Count": 6.0}
{"Video ID": "x1lAcT3xl5M", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #4 - Train With Next Sentence Prediction (NSP)", "Time Created": "2021-05-27 15:52:57 UTC", "Time Published": "2021-05-27 16:15:39 UTC", "Duration": "2205 seconds", "Description": "Next sentence prediction (NSP) is one-half of the training process behind the BERT model (the other being masked-language modeling\u200a-\u200aMLM).\n\nAlthough NSP (and MLM) are used to pre-train BERT models, we can use these exact methods to further pre-train our models to better understand the specific style of language in our own use cases.\n\nSo, in this video, we'll cover exactly how we take an unstructured body of text, and use it to pre-train a BERT model using NSP.\n\nMeditations data:\nhttps://github.com/jamescalam/transformers/blob/main/data/text/meditations/clean.txt\n\nJupyter Notebook\nhttps://github.com/jamescalam/transformers/blob/main/course/training/06_nsp_training.ipynb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/bert-for-next-sentence-prediction-466b67f8226f?sk=3595968413abde1c5833e1a96e449673\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 95.0, "Dislike Count": 1.0}
{"Video ID": "5-A435hIYio", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "New Features in Python 3.10", "Time Created": "2021-06-03 16:41:56 UTC", "Time Published": "2021-06-08 15:00:02 UTC", "Duration": "800 seconds", "Description": "The Python 3.10 release has several new features like structural pattern matching, a new typing Union operator, and parenthesized context managers!\n\nPython 3.10 has now been released, here we test all of the best new features introduced.\n\nWe'll cover some of the most interesting additions to Python\u200a-\u200astructural pattern matching, parenthesized context managers, more typing, and the new and improved error messages.\n\nDownload the latest release:\nhttps://www.python.org/downloads/release/python-3100/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/whats-new-in-python-3-10-a757c6c69342\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/whats-new-in-python-3-10-a757c6c69342?sk=648ae12c1025a83affba4eecec0d46c6\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:45 Type Annotations in Python\n01:10  Typing Union Operator\n02:07 Parenthesized Context Managers\n05:07 Structural Pattern Matching\n09:31 Better Error Messages", "Category": "Education", "Like Count": 375.0, "Dislike Count": 2.0}
{"Video ID": "IC9FaVPKlYc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training BERT #5 - Training With BertForPretraining", "Time Created": "2021-06-04 05:13:06 UTC", "Time Published": "2021-06-15 15:00:19 UTC", "Duration": "1306 seconds", "Description": "NSP Logic\nhttps://youtu.be/1gN1snKBLP0\n\nMLM Logic\nhttps://youtu.be/q9NS5WpfkrU\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-bert-aaad00533168\n\n\ud83d\udcd6 Here's a free link:\nhttps://towardsdatascience.com/how-to-train-bert-aaad00533168?sk=5ad4e5e44a6c573b3be1967c9abdcc35\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 128.0, "Dislike Count": 1.0}
{"Video ID": "fA0dFQacmic", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "FREE 11 Hour NLP Transformers Course (Next 3 Days Only)", "Time Created": "2021-06-04 07:56:44 UTC", "Time Published": "2021-06-04 13:00:19 UTC", "Duration": "267 seconds", "Description": "The offer has now expired! You can find the final 70% discount here:\nhttps://bit.ly/3DFvvY5\n\nIn total, 10823 people redeemed the code - which is incredible, I'm very happy so many of you were interested in the course and I hope it will help many of you in learning about transformers and NLP where it may have been too expensive to otherwise - so thank you all!\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery:\nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 51.0, "Dislike Count": 0.0}
{"Video ID": "GhGUZrcB-WM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How-to Use HuggingFace's Datasets - Transformers From Scratch #1", "Time Created": "2021-06-21 21:56:31 UTC", "Time Published": "2021-06-22 13:00:07 UTC", "Duration": "861 seconds", "Description": "How can we build our own custom transformer models?\n\nMaybe we'd like our model to understand a less common language, how many transformer models out there have been trained on Piemontese or the Nahuatl languages?\n\nIn that case, we need to do something different. We need to build our own model\u200a-\u200afrom scratch.\n\nIn this video, we'll learn how to use HuggingFace's datasets library to download multilingual data and prepare it for training our custom transformer tokenizer and model.\n\n---\nPart 2: https://youtu.be/JIeAB8vvBQo\nPart 3: https://youtu.be/heTYbpr9mD8\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403?sk=aea909609f41be43bdb2dbbd75a801f2\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 147.0, "Dislike Count": 3.0}
{"Video ID": "JIeAB8vvBQo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Build a Custom Transformer Tokenizer - Transformers From Scratch #2", "Time Created": "2021-06-22 20:07:37 UTC", "Time Published": "2021-06-24 14:00:06 UTC", "Duration": "857 seconds", "Description": "How can we build our own custom transformer models?\n\nMaybe we'd like our model to understand a less common language, how many transformer models out there have been trained on Piemontese or the Nahuatl languages?\n\nIn that case, we need to do something different. We need to build our own model\u200a-\u200afrom scratch.\n\nIn this video, we'll learn how to use HuggingFace's tokenizers library to build our own custom transformer tokenizer.\n\nPart 1: https://youtu.be/GhGUZrcB-WM\n---\nPart 3: https://youtu.be/heTYbpr9mD8\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/transformers-from-scratch-creating-a-tokenizer-7d7418adb403?sk=aea909609f41be43bdb2dbbd75a801f2\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 80.0, "Dislike Count": 3.0}
{"Video ID": "ziiF1eFM3_4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)", "Time Created": "2021-06-28 13:25:28 UTC", "Time Published": "2021-06-29 13:00:23 UTC", "Duration": "1764 seconds", "Description": "Vector similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together.\n\nSimilarity search is a complex topic and there are countless techniques for building effective search engines.\n\nIn this video, we'll cover three vector-based approaches for comparing languages and identifying similar 'documents', covering both vector similarity search and semantic search:\n\n- TF-IDF\n- BM25\n- Sentence-BERT\n\n\ud83d\udcf0 Original article:\nhttps://www.pinecone.io/learn/semantic-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n01:37 TF-IDF\n11:44 BM25\n20:30 SBERT", "Category": "Education", "Like Count": 415.0, "Dislike Count": 1.0}
{"Video ID": "AY62z7HrghY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "3 Traditional Methods for Similarity Search (Jaccard, w-shingling, Levenshtein)", "Time Created": "2021-06-28 17:44:01 UTC", "Time Published": "2021-06-29 12:00:04 UTC", "Duration": "1520 seconds", "Description": "Similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together.\n\nSimilarity search is a complex topic and there are countless techniques for building effective search engines.\n\nIn this video, we'll cover three traditional approaches for comparing languages and identifying similar 'documents':\n\n- Jaccard Similarity\n- w-shingling\n- Levenshtein distance\n\n\ud83d\udcf0 Original article:\nhttps://www.pinecone.io/learn/semantic-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:23 Jaccard Similarity\n02:39 w-shingling\n07:17 Levenshtein Distance", "Category": "Education", "Like Count": 86.0, "Dislike Count": 0.0}
{"Video ID": "heTYbpr9mD8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building MLM Training Input Pipeline - Transformers From Scratch #3", "Time Created": "2021-07-02 15:28:46 UTC", "Time Published": "2021-07-05 14:00:30 UTC", "Duration": "1392 seconds", "Description": "The input pipeline of our training process is the more complex part of the entire transformer build. It consists of us taking our raw OSCAR training data, transforming it, and preparing it for Masked-Language Modeling (MLM). Finally, we load our data into a DataLoader ready for training!\n\nPart 1: https://youtu.be/GhGUZrcB-WM\nPart 2: https://youtu.be/JIeAB8vvBQo\n---\nPart 4: https://youtu.be/35Pdoyi6ZoQ\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6\n\n\ud83d\udcd6 Free link:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6?sk=9db6224efbd4ec6fd407a80b528e69b0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Education", "Like Count": 69.0, "Dislike Count": 0.0}
{"Video ID": "ee71R4Cqb5o", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Angular App Setup With Material - Stoic Q&A #5", "Time Created": "2021-07-05 08:50:04 UTC", "Time Published": "2021-07-20 14:00:28 UTC", "Duration": "814 seconds", "Description": "\u25b6\ufe0f Stoic Q&A App Playlist: https://www.youtube.com/playlist?list=PLIUOU7oqGTLixb-CatMxNCO-mJioMmZEB\n\nThe fifth video in our Stoic Q&A series - setting up our Angular app with Angular Material.\n\nPrerequisites:\nInstallation of Node.js and NPM - https://nodejs.org/en/\nAngular - https://angular.io/guide/setup-local\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 17.0, "Dislike Count": 0.0}
{"Video ID": "35Pdoyi6ZoQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Training and Testing an Italian BERT - Transformers From Scratch #4", "Time Created": "2021-07-05 18:22:41 UTC", "Time Published": "2021-07-06 13:00:03 UTC", "Duration": "1838 seconds", "Description": "We need two things for training, our DataLoader and a model. The DataLoader we have \u2014 but no model.\n\nFor training, we need a raw (not pre-trained) RobertaForMaskedLM. To create that, we first need to create a RoBERTa config object to describe the parameters we\u2019d like to initialize FiliBERTo with.\n\nOnce we have our model, we set up our training loop and train!\n\nPost-training, we'll test the model with Laura, who is Italian - and hope for the best.\n\nPart 1: https://youtu.be/GhGUZrcB-WM\nPart 2: https://youtu.be/JIeAB8vvBQo\nPart 3: https://youtu.be/heTYbpr9mD8\n---\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/how-to-train-a-bert-model-from-scratch-72cfce554fc6?sk=9db6224efbd4ec6fd407a80b528e69b0\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n00:35 Review of Code\n02:02 Config Object\n06:28 Setup For Training\n10:30 Training Loop\n14:57 Dealing With CUDA Errors\n16:17 Training Results\n19:52 Loss\n21:18 Fill-mask Pipeline For Testing\n21:54 Testing With Laura", "Category": "Science & Technology", "Like Count": 94.0, "Dislike Count": 1.0}
{"Video ID": "sKyvsdEv6rk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Faiss - Introduction to Similarity Search", "Time Created": "2021-07-09 13:47:26 UTC", "Time Published": "2021-07-13 15:00:19 UTC", "Duration": "1896 seconds", "Description": "Full Similarity Search Playlist:\nhttps://www.youtube.com/watch?v=AY62z7HrghY&list=PLIUOU7oqGTLhlWpTz4NnuT3FekouIVlqc&index=1\n\nFacebook AI Similarity Search (FAISS) is one of the most popular implementations of efficient similarity search, but what is it\u200a-\u200aand how can we use it?\n\nWhat is it that makes FAISS special? How do we make the best use of this incredible tool?\n\nFortunately, it's a brilliantly simple process to get started with. And in this video, we'll explore some of the options FAISS provides, how they work, and\u200a-\u200amost importantly\u200a-\u200ahow FAISS can make our semantic search faster.\n\n\ud83c\udf32 Pinecone Article:\nhttps://www.pinecone.io/learn/faiss-tutorial/\n\n\ud83d\udcca Data:\nhttps://github.com/jamescalam/data/tree/main/sentence_embeddings_15K\n\nNotebook:\nhttps://gist.github.com/jamescalam/7117aa92235a7f52141ad0654795aa48\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 354.0, "Dislike Count": 5.0}
{"Video ID": "bWLvGGJLzF8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Why are there so many Tokenization methods in HF Transformers?", "Time Created": "2021-07-27 07:12:07 UTC", "Time Published": "2021-07-27 14:00:10 UTC", "Duration": "1080 seconds", "Description": "HuggingFace's transformers library is the de-facto standard for NLP\u200a-\u200aused by practitioners worldwide, it's powerful, flexible, and easy to use. It achieves this through a fairly large (and complex) code-base, which has resulted in the question:\n\n\"Why are there so many tokenization methods in HuggingFace transformers?\"\n\nTokenization is the process of encoding a string of text into transformer-readable token ID integers. In this video we cover five different methods for this - do these all produce the same output, or is there a difference between them?\n\n\ud83d\udcd9 Medium article:\nhttps://towardsdatascience.com/why-are-there-so-many-tokenization-methods-for-transformers-a340e493b3a8\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 If membership is too expensive - here's a free link:\nhttps://towardsdatascience.com/why-are-there-so-many-tokenization-methods-for-transformers-a340e493b3a8?sk=4a7e8c88d331aef9103e153b5b799ff5\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 51.0, "Dislike Count": 0.0}
{"Video ID": "B7wmo_NImgM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Choosing Indexes for Similarity Search (Faiss in Python)", "Time Created": "2021-08-09 14:33:47 UTC", "Time Published": "2021-08-09 15:04:10 UTC", "Duration": "1893 seconds", "Description": "Facebook AI Similarity Search (Faiss) is a game-changer in the world of search. It allows us to efficiently search a huge range of media, from GIFs to articles\u200a-\u200awith incredible accuracy in sub-second timescales for billion+ size datasets.\n\nThe success in Faiss is due to many reasons. One of those, in particular, is its flexibility. Faiss recognizes that there is no 'one-size-fits-all' in similarity search.\n\nInstead, Faiss comes with a wide range of search indexes\u200a-\u200awhich we can mix and match to our choosing.\n\nHowever, this great flexibility produces a question\u200a-\u200ahow do we know which size fits our use case?\n\nWhich index do we choose? Should we use multiple indexes, or is one enough?\n\nThis video will explore the pros and cons of some of the most important indexes\u200a-\u200aFlat, LSH, HNSW, and IVF. We will learn how we decide which to use and the impact of parameters in each index to build some of the best indexes for semantic search.\n\n\ud83c\udf32 Pinecone Article:\nhttps://www.pinecone.io/learn/vector-indexes/\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\nDownload script for Sift1M dataset:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nSimilarity Search Series:\nhttps://www.youtube.com/playlist?list=PLIUOU7oqGTLhlWpTz4NnuT3FekouIVlqc\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udc7e Discord\nhttps://discord.gg/c5QtDB9RAP\n\nMining Massive Datasets Book (Similarity Search):\n\ud83d\udcda https://amzn.to/3CC0zrc (3rd ed)\n\ud83d\udcda https://amzn.to/3AtHSnV (1st ed, cheaper)\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 122.0, "Dislike Count": 1.0}
{"Video ID": "e_SBq3s20M8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Locality Sensitive Hashing (LSH) for Search with Shingling + MinHashing (Python)", "Time Created": "2021-08-19 16:53:50 UTC", "Time Published": "2021-08-20 16:00:16 UTC", "Duration": "1627 seconds", "Description": "Locality sensitive hashing (LSH) is a widely popular technique used in approximate nearest neighbor (ANN) search. The solution to efficient similarity search is a profitable one\u200a-\u200ait is at the core of several billion (and even trillion) dollar companies.\n\nLSH consists of a variety of different methods. In this video, we'll be covering the traditional approach\u200a-\u200awhich consists of multiple steps\u200a-\u200ashingling, MinHashing, and the final banded LSH function.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff\n\n00:00 Intro\n01:21 Overview\n05:58 Shingling\n08:45 Vocab\n09:27 One-hot Encoding\n11:10 MinHash\n15:51 Signature Info\n18:08 LSH\n22:20 Tuning LSH", "Category": "Science & Technology", "Like Count": 208.0, "Dislike Count": 19.0}
{"Video ID": "8bOrMqEdfiQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How LSH Random Projection works in search (+Python)", "Time Created": "2021-08-24 05:09:11 UTC", "Time Published": "2021-08-24 16:00:04 UTC", "Duration": "1148 seconds", "Description": "Locality sensitive hashing (LSH) is a widely popular technique used in approximate similarity search. The solution to efficient similarity search is a profitable one\u200a-\u200ait is at the core of several billion (and even trillion) dollar companies.\n\nThe problem with similarity search is scale. Many companies deal with millions-to-billions of data points every single day. Given a billion data points, is it feasible to compare all of them with every search?\n\nFurther, many companies are not performing single searches\u200a-\u200aGoogle deals with more than 3.8 million searches every minute.\n\nBillions of data points combined with high-frequency searches are problematic\u200a-\u200aand we haven't considered the dimensionality nor the similarity function itself. Clearly, an exhaustive search across all data points is unrealistic for larger datasets.\n\nThe solution to searching impossibly huge datasets? Approximate search. Rather than exhaustively comparing every pair, we approximate\u200a-\u200arestricting the search scope only to high probability matches.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing-random-projection/\n\nDownload Sift1M:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nIndexLSH for Fast Similarity Search in Faiss:\nhttps://youtu.be/ZLfdQq_u7Eo\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 66.0, "Dislike Count": 3.0}
{"Video ID": "ZLfdQq_u7Eo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "IndexLSH for Fast Similarity Search in Faiss", "Time Created": "2021-08-24 05:25:21 UTC", "Time Published": "2021-08-24 16:00:12 UTC", "Duration": "1119 seconds", "Description": "Faiss \u200a- \u200aor Facebook AI Similarity Search\u200a - \u200ais an open-source framework built for enabling similarity search.\n\nFaiss has many super-efficient implementations of different indexes that we can use in similarity search. That long list of indexes includes IndexLSH\u200a-\u200aan easy-to-use implementation of everything we have covered so far in LSH.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/locality-sensitive-hashing-random-projection/\n\nDownload Sift1M:\nhttps://gist.github.com/jamescalam/a09a16c17b677f2cf9c019114711f3bf\n\nHow LSH Random Projection works in search (+Python):\nhttps://youtu.be/8bOrMqEdfiQ\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 27.0, "Dislike Count": 0.0}
{"Video ID": "BMYBwbkbVec", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Faiss - Vector Compression with PQ and IVFPQ (in Python)", "Time Created": "2021-08-30 14:35:01 UTC", "Time Published": "2021-08-30 15:30:04 UTC", "Duration": "1161 seconds", "Description": "So far we\u2019ve worked through the logic behind a simple, readable implementation of product quantization (PQ) in Python for semantic search. Realistically we wouldn\u2019t use this because it is not optimized and we already have excellent implementations elsewhere. Instead, we would use a library like Faiss (Facebook AI Similarity Search) \u2014 or a production-ready service like Pinecone.\n\nWe\u2019ll take a look at how we can build a PQ index in Faiss, and we\u2019ll even take a look at combining PQ with an Inverted File (IVF) step to improve search speed.\n\nBefore we start, we need to get data. We will be using the Sift1M dataset. It can be downloaded and opened using this script:\nhttps://gist.github.com/jamescalam/928a374b85daffa49a565f3dc18d059c#file-get_sift1m-ipynb\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/product-quantization/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 36.0, "Dislike Count": 1.0}
{"Video ID": "t9mRf2S5vDI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Product Quantization for Vector Similarity Search (+ Python)", "Time Created": "2021-08-30 15:22:47 UTC", "Time Published": "2021-08-30 15:37:46 UTC", "Duration": "1777 seconds", "Description": "Vector similarity search can require huge amounts of memory. Indexes containing 1M dense vectors (a small dataset in today\u2019s world) will often require several GBs of memory to store. When building recommendation systems or semantic search engines, this is not acceptable.\n\nThe problem of excessive memory usage is exasperated by high-dimensional data, and with ever-increasing dataset sizes, this can very quickly become unmanageable.\n\nProduct quantization (PQ) is a popular method for dramatically compressing high-dimensional vectors to use 97% less memory, and for making nearest-neighbor search speeds 5.5x faster in our tests.\n\nA composite IVF+PQ index speeds up the search by another 16.5x without affecting accuracy, for a whopping total speed increase of 92x compared to non-quantized indexes.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/product-quantization/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free AI-Powered Code Refactoring with Sourcery: \nhttps://sourcery.ai/?utm_source=YouTub&utm_campaign=JBriggs&utm_medium=aff", "Category": "Science & Technology", "Like Count": 116.0, "Dislike Count": 2.0}
{"Video ID": "GEhmmcx1lvM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Composite Indexes and the Faiss Index Factory", "Time Created": "2021-09-11 17:27:12 UTC", "Time Published": "2021-09-24 12:53:58 UTC", "Duration": "1063 seconds", "Description": "In the world of vector search, there are many indexing methods and vector processing techniques that allow us to prioritize between recall, latency, and memory usage.\n\nUsing specific methods such as IVF, PQ, or HNSW, we can often return good results. But for best performance we will usually want to use composite indexes.\n\nWe can view a composite index as a step-by-step process of vector transformations and one or more indexing methods. Allowing us to place multiple indexes and/or processing steps together to create our \u2018ideal\u2019 index.\n\nFor example, we can use an inverted file (IVF) index to reduce the scope of our search (increasing search speed), and then add a compression technique such as product quantization (PQ) to keep larger indexes within a reasonable size limit.\n\nWhere there is the ability to customize indexes, there is the risk of producing indexes with unnecessarily poor recall, latency, or memory usage.\n\nWe must know how composite indexes work if we want to build robust and high-performance vector similarity search applications. It is essential to understand where different indexes or vector transformations can be used \u2014 and when they are not needed.\n\nPart 2: https://youtu.be/3Wqh4iUupbM\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/composite-indexes/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:54 Composite Indexes\n06:43 Faiss Index Factory\n11:34 Why we use Index Factory\n17:11 Outro", "Category": "Science & Technology", "Like Count": 21.0, "Dislike Count": 0.0}
{"Video ID": "3Wqh4iUupbM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Best Indexes for Similarity Search in Faiss", "Time Created": "2021-09-12 07:02:26 UTC", "Time Published": "2021-09-24 12:54:07 UTC", "Duration": "1582 seconds", "Description": "In the world of vector search, there are many indexing methods and vector processing techniques that allow us to prioritize between recall, latency, and memory usage.\n\nUsing specific methods such as IVF, PQ, or HNSW, we can often return good results. But for best performance we will usually want to use composite indexes.\n\nWe can view a composite index as a step-by-step process of vector transformations and one or more indexing methods. Allowing us to place multiple indexes and/or processing steps together to create our \u2018ideal\u2019 index.\n\nFor example, we can use an inverted file (IVF) index to reduce the scope of our search (increasing search speed), and then add a compression technique such as product quantization (PQ) to keep larger indexes within a reasonable size limit.\n\nWhere there is the ability to customize indexes, there is the risk of producing indexes with unnecessarily poor recall, latency, or memory usage.\n\nWe must know how composite indexes work if we want to build robust and high-performance vector similarity search applications. It is essential to understand where different indexes or vector transformations can be used \u2014 and when they are not needed.\n\nPart 1: https://youtu.be/GEhmmcx1lvM\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/composite-indexes/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:30 IVFADC\n03:30 IVFADC in Faiss\n07:29 Multi-D-ADC\n09:17 Multi-D-ADC in Faiss\n14:43 IVF-HNSW\n21:39 IVF-HNSW in Faiss\n25:58 Outro", "Category": "Science & Technology", "Like Count": 31.0, "Dislike Count": 0.0}
{"Video ID": "cR4qMSIvX28", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build a Bert WordPiece Tokenizer in Python and HuggingFace", "Time Created": "2021-09-13 20:13:08 UTC", "Time Published": "2021-09-14 13:30:06 UTC", "Duration": "1880 seconds", "Description": "Building a transformer model from scratch can often be the only option for many more specific use cases. Although BERT and other transformer models have been pre-trained for a vast number of languages and domains, they do not cover everything.\n\nOften, it is these less common use cases that stand to gain the most from having someone come along and build a specific transformer model. It could be for an uncommon language or less tech-savvy domain.\n\nBERT is the most popular transformer for a wide range of language-based machine learning\u200a-\u200afrom sentiment analysis to question and answering, BERT has enabled a diverse range of innovation across many borders and industries.\n\nThe first step for many in designing a new BERT model is the tokenizer. In this article, we'll take a look at the WordPiece tokenizer used by BERT\u200a-\u200aand see how we can build our own from scratch.\n\n\ud83d\udcd5 Medium article:\nhttps://towardsdatascience.com/how-to-build-a-wordpiece-tokenizer-for-bert-f505d97dddbb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd79\ufe0f Free Article link (if you don't have Medium membership): \nhttps://towardsdatascience.com/how-to-build-a-wordpiece-tokenizer-for-bert-f505d97dddbb?sk=eea06e01c9faecd939e10589e9de1291", "Category": "Science & Technology", "Like Count": 95.0, "Dislike Count": 1.0}
{"Video ID": "H_kJDHvu-v8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Metadata Filtering for Vector Search + Latest Filter Tech", "Time Created": "2021-09-20 12:23:11 UTC", "Time Published": "2021-09-20 14:04:27 UTC", "Duration": "2054 seconds", "Description": "Vector similarity search makes massive datasets searchable in fractions of a second. Yet despite the brilliance and utility of this technology, often what seem to be the most straightforward problems are the most difficult to solve. Such as filtering.\n\nFiltering takes the top place in being seemingly simple \u2014 but actually incredibly complex. Applying fast-but-accurate filters when performing a vector search (ie, nearest-neighbor search) on massive datasets is a surprisingly stubborn problem.\n\nThis article explains the two common methods for adding filters to vector search, and their serious limitations. Then we will explore Pinecone\u2019s solution to filtering in vector search.\n\n\ud83d\udce3 Get the API key!\nhttps://www.pinecone.io/start/\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/vector-search-filtering/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:24 Vector Search Recap\n02:03 Why Filter?\n02:56 Metadata Filtering 101\n07:48 Pre-filtering\n09:37 Post-filtering\n11:30 Single-Stage Filtering\n12:22 Vectors and Metadata Code\n13:58 Connecting to Pinecone\n14:55 Building Query Vector\n16:47 Querying\n21:37 First Filter\n24:40 Adding More Conditions\n27:03 Filtering with Numbers\n30:55 Search Speed and Filtering\n33:44 Outro", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "r-zQQ16wTCA", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Build NLP Pipelines with HuggingFace Datasets", "Time Created": "2021-09-20 14:58:03 UTC", "Time Published": "2021-09-23 13:30:07 UTC", "Duration": "2030 seconds", "Description": "HF Datasets is an essential tool for NLP practitioners\u200a-\u200ahosting over 1.4K (mostly) high-quality language-focused datasets, and an easy-to-use treasure trove of functions for building efficient pre-processing pipelines.\n\nIn this article, we will take a look at the massive repository of datasets available, and explore some of the library's brilliant data processing capabilities.\n\n\ud83d\udcd5 Medium article:\nhttps://towardsdatascience.com/build-nlp-pipelines-with-huggingface-datasets-d597ff5f68ad\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free Article Access (if you don't have Medium membership!): \nhttps://towardsdatascience.com/build-nlp-pipelines-with-huggingface-datasets-d597ff5f68ad?sk=948106e47e64bc3e9e8a1358b0568d48", "Category": "Science & Technology", "Like Count": 53.0, "Dislike Count": 1.0}
{"Video ID": "QvKMwLjdK-s", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "HNSW for Vector Search Explained and Implemented with Faiss (Python)", "Time Created": "2021-09-29 08:13:49 UTC", "Time Published": "2021-10-05 13:00:23 UTC", "Duration": "2075 seconds", "Description": "Hierarchical Navigable Small World (HNSW) graphs are among the top-performing indexes for vector similarity search. HNSW is a hugely popular technology that time and time again produces state-of-the-art performance with super-fast search speeds and flawless recall \u2014 HNSW is not to be missed.\n\nDespite being a popular and robust algorithm for approximate nearest neighbors (ANN) searches, understanding how it works is far from easy.\n\nThis video helps demystify HNSW and explains this intelligent algorithm in an easy-to-understand way. Towards the end of the video, we'll look at how to implement HNSW using Faiss and which parameter settings give us the performance we need.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/hnsw/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:41 Foundations of HNSW\n08:41 How HNSW Works\n16:38 The Basics of HNSW in Faiss\n21:40 How Faiss Builds an HNSW Graph\n26.49 Building the Best HNSW Index\n33:33 Fine-tuning HNSW\n34:30 Outro", "Category": "Science & Technology", "Like Count": 131.0, "Dislike Count": 3.0}
{"Video ID": "g_yMowQikOE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to APIs in Python - API Series #1", "Time Created": "2021-09-29 12:21:47 UTC", "Time Published": "2021-09-29 14:00:18 UTC", "Duration": "1704 seconds", "Description": "Taking those first steps into interacting with the web using Python can seem daunting\u200a-\u200abut it need not be. It is a surprisingly simple process, with well established rules and guidelines.\n\nWe'll cover the absolute essentials for getting started, including:\n\n- Application Program Interfaces (APIs)\n- Javascript Object Notation (JSON)\n- Requests with Python\n- Real world use-cases\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/quick-fire-guide-to-apis-in-python-891dd98c8877\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Sign-up For New Articles Every Week on Medium!\nhttps://jamescalam.medium.com/subscribe (it's free!)\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free Access Link (if you don't have Medium membership): \nhttps://towardsdatascience.com/quick-fire-guide-to-apis-in-python-891dd98c8877?sk=7c159ba45154db23abcc6a7f9de4f910\n\nGeocoding Docs:\nhttps://developers.google.com/maps/documentation/geocoding/cloud-setup\n\nGitHub Docs:\nhttps://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token\n\n00:00 Intro\n00:20 What is an API?\n01:47 RESTful APIs\n05:26 API Methods\n07:20 HTTP Codes (200s)\n08:14 HTTP Codes (400s)\n10:00 JSON Format\n11:21 Talking to APIs in Python\n14:30 Google Geocoding API\n22:08 GitHub API\n27:48 Outro", "Category": "Science & Technology", "Like Count": 119.0, "Dislike Count": 0.0}
{"Video ID": "bVZJ_O_-0RE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to Dense Vectors for NLP and Vision", "Time Created": "2021-10-04 08:28:38 UTC", "Time Published": "2021-10-12 17:47:15 UTC", "Duration": "2629 seconds", "Description": "There is perhaps no greater component to the success of modern Natural Language Processing (NLP) technology than vector representations of language. The meteoric early 2010s rise of NLP was ignited with the introduction of word2vec by a team lead by Tom\u00e1\u0161 Mikolov in 2013.\n\nWord2vec is one of the most iconic and earliest examples of dense vectors representing text. But since the days of word2vec, developments in representing language have advanced at ludicrous speeds.\n\nThis video will explore *why* we use dense vectors \u2014 and some of the best approaches to building dense vectors available today.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/dense-vector-embeddings-nlp/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:50 Why Dense Vectors?\n03:55 Word2vec and Representing Meaning\n08:40 Sentence Transformers\n09:58 Sentence Transformers in Python\n15:08 Question-Answering\n18:18 DPR in Python\n29:55 Vision Transformers\n33:22 OpenAI's CLIP in Python\n42:49 Review and What's Next", "Category": "Science & Technology", "Like Count": 92.0, "Dislike Count": 0.0}
{"Video ID": "MF75aNH3Gjs", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "API Series #2 - Building an API with Flask in Python", "Time Created": "2021-10-05 07:01:25 UTC", "Time Published": "2021-10-07 14:52:32 UTC", "Duration": "1902 seconds", "Description": "Next video - how to deploy to the cloud: https://youtu.be/3fsIcMgUOY8\n\nHow can we set up a way to communicate from one software instance to another? It sounds simple, and \u2014 to be completely honest \u2014 it is.\n\nAll we need is an API.\n\nAn API (Application Programming Interface) is a simple interface that defines the types of requests (demands/questions, etc.) that can be made, how they are made, and how they are processed.\n\nIn our case, we will be building an API that allows us to send a range of GET/POST/PUT/PATCH/DELETE requests (more on this later), to different endpoints, and return or modify data connected to our API.\n\nWe will be using the Flask framework to create our API and Insomnia to test it.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83d\udd79\ufe0f Medium article:\nhttps://towardsdatascience.com/the-right-way-to-build-an-api-with-python-cd08ab285f8f\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\nFree article link: \nhttps://towardsdatascience.com/the-right-way-to-build-an-api-with-python-cd08ab285f8f?sk=6e2dda4c8b6012767114e12ff34b1464\n\nDownload Insomnia:\nhttps://insomnia.rest/download", "Category": "Science & Technology", "Like Count": 117.0, "Dislike Count": 2.0}
{"Video ID": "WS1uVMGhlWQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Intro to Sentence Embeddings with Transformers", "Time Created": "2021-10-19 09:44:58 UTC", "Time Published": "2021-10-20 17:06:20 UTC", "Duration": "1866 seconds", "Description": "Transformers have wholly rebuilt the landscape of natural language processing (NLP). Before transformers, we had okay translation and language classification thanks to recurrent neural nets (RNNs) \u2014 their language comprehension was limited and led to many minor mistakes, and coherence over larger chunks of text was practically impossible.\n\nSince the introduction of the first transformer model in the 2017 paper \u2018Attention is all you need\u2019, NLP has moved from RNNs to models like BERT and GPT. These new models can answer questions, write articles (maybe GPT-3 wrote this), enable incredibly intuitive semantic search \u2014 and much more.\n\nIn this video, we will explore how these embeddings have been adapted and applied to a range of semantic similarity applications by using a new breed of transformers called \u2018sentence transformers\u2019.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/sentence-embeddings/\n\nVectors in ML:\nhttps://www.youtube.com/playlist?list=PLIUOU7oqGTLgz-BI8bNMVGwQxIMuQddJO\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 188.0, "Dislike Count": 1.0}
{"Video ID": "aSx0jg9ZILo", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fine-tune Sentence Transformers the OG Way (with NLI Softmax loss)", "Time Created": "2021-10-22 14:16:49 UTC", "Time Published": "2021-10-22 14:39:46 UTC", "Duration": "2223 seconds", "Description": "Sentence embeddings with transformers can be used across a range of applications, such as semantic textual similarity (STS), semantic clustering, or information retrieval (IR) using concepts rather than words.\n\nThis video dives deeper into the training process of the first sentence transformer, sentence-BERT, or more commonly known as SBERT. We will explore the Natural Language Inference (NLI) training approach of softmax loss to fine-tune models for producing sentence embeddings.\n\nBe aware that softmax loss is no longer the preferred approach to training sentence transformers and has been superseded by other methods such as MSE margin and multiple negatives ranking loss. But we\u2019re covering this training method as an important milestone in the development of ever-improving sentence embeddings.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/train-sentence-transformers-softmax/\n\nCheck out the Sentence Transformers library:\nhttps://github.com/UKPLab/sentence-transformers\n\nTalk by Nils Reimers (one of the SBERT creators) on training:\nhttps://www.youtube.com/watch?v=RHXZKUr8qOY\n\nHe does more NLP vids too:\nhttps://www.youtube.com/channel/UC1zCuTrfpjT6Sv2kJk-JkvA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:42 NLI Fine-tuning\n01:44 Softmax Loss Training Overview\n05:47 Preprocessing NLI Data\n12:48 PyTorch Process\n19:48 Using Sentence-Transformers\n30:45 Results\n35:49 Outro", "Category": "Science & Technology", "Like Count": 83.0, "Dislike Count": 0.0}
{"Video ID": "or5ew7dqA-c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fine-tune High Performance Sentence Transformers (with Multiple Negatives Ranking)", "Time Created": "2021-10-25 20:18:30 UTC", "Time Published": "2021-10-26 13:00:22 UTC", "Duration": "2213 seconds", "Description": "Transformer-produced sentence embeddings have come a long way in a very short time. Starting with the slow but accurate similarity prediction of BERT cross-encoders, the world of sentence embeddings was ignited with the introduction of SBERT in 2019. Since then, many more sentence transformers have been introduced. These models quickly made the original SBERT obsolete.\n\nHow did these newer sentence transformers manage to outperform SBERT so quickly? The answer is multiple negatives ranking (MNR) loss.\n\nThis video will cover what MNR loss is, the data it requires, and how to implement it to fine-tune our own high-quality sentence transformers.\n\nImplementation will cover two approaches. The first is more involved, and outlines the exact steps to fine-tune the model (we'll just run over it quickly). The second approach makes use of the sentence-transformers library\u2019s excellent utilities for fine-tuning.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/fine-tune-sentence-transformers-mnr/\n\nCheck out the Sentence Transformers library:\nhttps://github.com/UKPLab/sentence-transformers\n\nTalk by Nils Reimers (one of the SBERT creators) on training:\nhttps://www.youtube.com/watch?v=RHXZKUr8qOY\n\nHe does more NLP vids too:\nhttps://www.youtube.com/channel/UC1zCuTrfpjT6Sv2kJk-JkvA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:02 NLI Training Data\n02:56 Preprocessing\n10:11 SBERT Finetuning Visuals\n14:14 MNR Loss Visual\n16:37 MNR in PyTorch\n23:04 MNR in Sentence Transformers\n34:20 Results\n36:14 Outro", "Category": "Science & Technology", "Like Count": 86.0, "Dislike Count": 0.0}
{"Video ID": "iCkftKsnQgg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hybrid Search Walkthrough in Pinecone", "Time Created": "2021-10-29 01:44:06 UTC", "Time Published": "2021-10-29 15:05:00 UTC", "Duration": "1040 seconds", "Description": "Pinecone offers a production-ready vector database for high performance and reliable *semantic search* at scale. But did you know Pinecone's semantic search can be paired with the more traditional keyword search?\n\nSemantic search is a compelling technology allowing us to search using abstract concepts and *meaning* rather than relying on specific words. However, sometimes a simple keyword search can be just as valuable \u2014 especially if we know the exact wording of what we're searching for.\n\nIn this video, we will explore these features through a start-to-finish example of basic keyword search in Pinecone.\n\n\ud83c\udf32 Check the docs:\nhttps://www.pinecone.io/docs/examples/basic-hybrid-search/\n\n\ud83d\udd11 Free API key:\nhttps://app.pinecone.io\n\n00:52 How Hybrid Search Works\n01:25 Preprocessing\n03:01 Creating Keywords\n05:34 Creating an Index\n06:50 Data Upsert\n08:33 Query Setup\n10:52 Keyword Search\n12:31 OR Logic\n14:49 AND Logic\n15:10 Negation\n17:04 Outro", "Category": "Science & Technology", "Like Count": 17.0, "Dislike Count": 1.0}
{"Video ID": "3fsIcMgUOY8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "API Series #3 - How to Deploy Flask APIs to the Cloud (GCP)", "Time Created": "2021-11-01 23:16:31 UTC", "Time Published": "2021-11-02 14:30:00 UTC", "Duration": "806 seconds", "Description": "Building that first API is for many of us, a significant step towards creating impactful tools that may one day be used by many developers. But often those APIs don't make it out of our local machines.\n\nFortunately, it's incredibly easy to deploy APIs. Assuming you have no idea what you're doing right now\u200a-\u200ayou will probably be deploying your first API in around ten minutes.\n\nI'm not joking, it's super easy. Let's get started.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/how-to-deploy-a-flask-api-8d54dd8d8b8a\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udcd6 Free article link:\nTO ADD", "Category": "Science & Technology", "Like Count": 75.0, "Dislike Count": 2.0}
{"Video ID": "NNS5pOpjvAQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "All You Need to Know on Multilingual Sentence Vectors (1 Model, 50+ Languages)", "Time Created": "2021-11-04 11:27:18 UTC", "Time Published": "2021-11-04 13:00:10 UTC", "Duration": "2392 seconds", "Description": "We\u2019ve learned about how sentence transformers can be used to create high-quality vector representations of text. We can then use these vectors to find similar vectors, which can be used for many applications such as semantic search or topic modeling.\n\nThese models are very good at producing meaningful, information-dense vectors. But they don\u2019t allow us to compare sentences across different languages.\n\nOften this may not be a problem. However, the world is becoming increasingly interconnected, and many companies span across multiple borders and languages. Naturally, there is a need for sentence vectors that are language agnostic.\n\nUnfortunately, very few textual similarity datasets span multiple languages, particularly for less common languages. And the standard training methods used for sentence transformers would require these types of datasets.\n\nDifferent approaches need to be used. Fortunately, some techniques allow us to extend models to other languages using more easily obtained language translations.\n\nIn this video, we will cover how multilingual models work and are built. We\u2019ll learn how to develop our own multilingual sentence transformers, the datasets to look for, and how to use high-performing pretrained multilingual models.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/multilingual-transformers/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:19 Multilingual Vectors\n05:55 Multi-task Training (mUSE)\n09:36 Multilingual Knowledge Distillation\n11:13 Knowledge Distillation Training\n13:43 Visual Walkthrough\n14:53 Parallel Data Prep\n20:23 Choosing a Student Model\n24:55 Initializing the Models\n30:05 ParallelSentencesDataset\n33:54 Loss and Fine-tuning\n36:59 Model Evaluation\n39:23 Outro", "Category": "Science & Technology", "Like Count": 30.0, "Dislike Count": 0.0}
{"Video ID": " -td57YvJdHc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Question-Answering in NLP (Extractive QA and Abstractive QA)", "Time Created": "2021-11-13 19:09:02 UTC", "Time Published": "2021-11-16 12:06:13 UTC", "Duration": "2886 seconds", "Description": "Search is a crucial functionality in many applications and companies globally. Whether in manufacturing, finance, healthcare, or *almost* any other industry, organizations have vast internal information and document repositories.\n\nUnfortunately, the scale of many companies\u2019 data means that the organization and accessibility of information can become incredibly inefficient. The problem is exacerbated for language-based information. Language is a tool for people to communicate often abstract ideas and concepts. Naturally, ideas and concepts are harder for a computer to comprehend and store in a meaningful way.\n\nHow do we minimize this problem? The answer lies with *semantic search*, specifically with the question-answering (QA) flavor of semantic search.\n\nThis article will introduce the different forms of QA, the components of these 'QA stacks', and where we might use them.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/question-answering/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Meaningful Search\n01:23 Use-case\n02:22 Open Domain QA (ODQA)\n06:41 SQuAD Format\n10:45 Quick Preprocessing\n15:18 Creating Context Vectors Database\n23:24 Open-book Extractive QA\n32:50 Open-book Abstractive QA\n41:53 Closed-book Abstractive QA\n47:27 Final Thoughts", "Category": "Science & Technology", "Like Count": 72.0, "Dislike Count": 0.0}
{"Video ID": "pNvujJ1XyeQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Today Unsupervised Sentence Transformers, Tomorrow Skynet (how TSDAE works)", "Time Created": "2021-11-24 14:20:20 UTC", "Time Published": "2021-11-24 16:24:24 UTC", "Duration": "2661 seconds", "Description": "To adapt a pretrained transformer to produce meaningful sentence vectors, we typically need a more supervised fine-tuning approach. We can use datasets like natural language inference (NLI) pairs, labeled semantic textual similarity (STS) data, or parallel data (pairs of translations).\n\nFor some domains and languages, such as finance and English, this data is fairly easy to find or gather. But many domains and many languages have very little labeled data. If you can find semantic similarity pairs for the agriculture industry, please let me know. There are many languages, such as Dhivehi, where unlabelled data is hard to find and labelled data practically non-existent.\n\nThis means you either spend a very long time gathering tens of thousands of labeled samples or you can try an unsupervised fine-tuning approach.\n\nUnsupervised training methods for sentence transformers are not as effective as their supervised counterparts, but they do work. And if you have no other choice, why not?\n\nIn this video, we will introduce the concept of unsupervised fine-tuning for sentence transformers. We will learn to train these models using the unsupervised Transformer-based Sequential Denoising Auto-Encoder (TSDAE) approach.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/unsupervised-training-sentence-transformers/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Why Language Embedding Matters\n05:12 Supervised Methods\n05:29 Natural Language Inference\n07:15 Semantic Textual Similarity\n07:43 Multilingual Training\n10:00 TSDAE (Unsupervised)\n18:50 Data Preparation\n29:05 Initialize Model\n32:39 Model Training\n36:25 NLTK Error\n37:15 Evaluation\n41:01 TSDAE vs Supervised Methods\n42:42 Why TSDAE is Cool", "Category": "Science & Technology", "Like Count": 70.0, "Dislike Count": 0.0}
{"Video ID": "3IPCEeh4xTg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Making The Most of Data: Augmented SBERT", "Time Created": "2021-12-16 15:46:03 UTC", "Time Published": "2021-12-17 14:24:40 UTC", "Duration": "3310 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nML models are data-hungry. They consume massive amounts of data to identify generalized patterns and apply those learned patterns to new data.\n\nAs models get bigger, so do datasets. And although we have seen an explosion of data in the past decade, it is often not accessible or in an ML-friendly format, especially in niche domains.\n\nFor many niche, low-resource domains, finding or annotating a substantial dataset manually is practically impossible.\n\nFortunately, we don't need to label (or even find) this new data. Instead, we can automatically generate or label data using one or more *data augmentation* techniques.\n\nIn this video, we will introduce data augmentation and its application to the field of NLP. We will focus on the 'in-domain' flavor of a particular data-augmentation strategy named augmented SBERT (AugSBERT).\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/data-augmentation/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 42.0, "Dislike Count": 0.0}
{"Video ID": "mjKqP3kRxbQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Building Transformer Tokenizers (Dhivehi NLP #1)", "Time Created": "2021-12-28 15:02:22 UTC", "Time Published": "2021-12-28 15:45:03 UTC", "Duration": "1982 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nGet in touch with Ashraq:\nhttps://www.linkedin.com/in/ismailashraq/\n\nThe language of Dhivehi (or Maldivian) is fascinating. It uses a complex writing system known as Thaana, and I absolutely cannot comprehend any of it. It is so wildly different from anything I know\u200a-\u200abut, like the archipelago, it looks wonderful.\n\nAshraq described the difficulty of applying NLP to his native tongue of Dhivehi. There are several reasons for this, which we will explore in this video, and learn how to build an effective Dhivehi WordPiece tokenizer.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/designing-tokenizers-for-low-resource-languages-7faa4ab30ef4\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Article Friend Link (Free Access):\nhttps://towardsdatascience.com/designing-tokenizers-for-low-resource-languages-7faa4ab30ef4?sk=c0c16de9eea7dbe1d2a9c106abf38e1a\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:06 Dhivehi Project\n02:28 Hurdles for Low Resource Domains\n04:21 Dhivehi Dataset\n04:52 Download Dhivehi Corpus\n08:25 Tokenizer Components\n08:44 Normalizer Component\n11:55 Pre-tokenization Component\n14:59 Post-tokenization Component\n16:26 Decoder Component\n17:41 Tokenizer Implementation\n21:04 Tokenizer Training\n24:22 Post-processing Implementation\n27:12 Decoder Implementation\n28:07 Saving for Transformers\n30:33 Tokenizer Test and Usage\n31:36 Download Dhivehi Models\n32:21 First Steps", "Category": "Science & Technology", "Like Count": 49.0, "Dislike Count": 0.0}
{"Video ID": "a8jyue22SJM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "AugSBERT: Domain Transfer for Sentence Transformers", "Time Created": "2022-01-04 05:14:16 UTC", "Time Published": "2022-01-04 14:59:50 UTC", "Duration": "1750 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nWhen building language models, we can spend months optimizing training and model parameters, but it\u2019s useless if we don't have the correct data.\n\nThe success of our language models relies first and foremost on data. The augmented SBERT training strategy can help us.\n\nGiven this scenario, we can transfer information from an out-of-domain (or *source*) dataset to our target domain. We will learn how to do this here. First, we will learn to assess which source datasets align best with our target domain quickly. Then we will explain and work through the AugSBERT domain-transfer training strategy.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/augsbert-domain-transfer/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83d\udd17 n-gram Similarity Script: https://gist.github.com/jamescalam/b73f37017ae32bd6094747c4b0fca94a\n\ud83d\udd17 AugSBERT In-Domain Article: https://www.pinecone.io/learn/data-augmentation/\n\n00:00 Why Use Domain Transfer\n04:08 Strategy Outline\n06:05 Train Source Cross-Encoder\n12:44 Cross-Encoder Outcome\n15:12 Labeling Target Data\n20:31 Training Bi-encoder\n23:58 Evaluator Bi-encoder Performance\n28:08 Final Points", "Category": "Science & Technology", "Like Count": 41.0, "Dislike Count": 0.0}
{"Video ID": "w1dMEWm7jBc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build a Q&A AI in Python (Open-domain Question-Answering)", "Time Created": "2022-01-10 07:19:13 UTC", "Time Published": "2022-01-11 14:00:20 UTC", "Duration": "2364 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nHow can we design these natural, human-like Q&A interfaces? The answer is open-domain question-answering (ODQA). ODQA allows us to use natural language to query a database.\n\nThat means that, given a dataset like a set of internal company documents, online documentation, or as is the case with Google, everything on the world\u2019s internet, we can retrieve relevant information in a natural, more human way.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/retriever-models/\n\n\ud83d\udd17 Nils YT Talk: https://youtu.be/XNJThigyvos?t=118\n\ud83d\udd17 MNR Loss Article: \n\ud83d\udd17 Free Pinecone API Key: https://app.pinecone.io/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Why QA\n04:05 Open Domain QA\n08:24 Do we need to fine-tune?\n11:44 How Retriever Training Works\n12:59 SQuAD Training Data\n16:29 Retriever Fine-tuning\n19:32 IR Evaluation\n25:58 Vector Database Setup\n33:42 Querying\n37:41 Final Notes", "Category": "Science & Technology", "Like Count": 66.0, "Dislike Count": 1.0}
{"Video ID": " -fzCSPsfMic", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build a Q&A Reader Model in Python (Open-domain QA)", "Time Created": "2022-01-18 12:17:09 UTC", "Time Published": "2022-01-18 16:37:37 UTC", "Duration": "1504 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nOpen-domain question-answering (ODQA) is a wildly popular *pipeline* of databases and language models that allow us to ask a machine human-like questions and return comprehensible and even intelligent answers.\n\nDespite the outward guise of simplicity, ODQA requires a reasonably advanced set of components placed together to enable the *extractive* Q&A functionality.\n\nWe call this *extractive* Q&A because the models are not generating an answer. Instead, the answer already exists but is hidden somewhere within potentially thousands, millions, or even more data sources.\n\nBy enabling extractive Q&A, we enable a more *intelligent* and *efficient* way to retrieve information from what can be massive stores of data.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/reader-models/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:13 ODQA Components\n03:09 Data Preprocessing\n22:35 Fine-tuning", "Category": "Science & Technology", "Like Count": 26.0, "Dislike Count": 0.0}
{"Video ID": "JLKUV-LiXjk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #1 - Installation and API", "Time Created": "2022-01-25 12:04:00 UTC", "Time Published": "2022-01-25 16:00:09 UTC", "Duration": "735 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 2:\nhttps://www.youtube.com/watch?v=U0EoaFFGyTg&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=2\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:39 App Outline\n03:36 Streamlit Installation\n06:15 Streamlit API Basics", "Category": "Science & Technology", "Like Count": 32.0, "Dislike Count": 0.0}
{"Video ID": "U0EoaFFGyTg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #2 - ML Models and APIs", "Time Created": "2022-01-26 16:07:51 UTC", "Time Published": "2022-01-26 16:30:36 UTC", "Duration": "911 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 3:\nhttps://www.youtube.com/watch?v=lYDiSCDcxmc&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=3\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\ud83d\udd17 Code to Create Index:\nhttps://gist.github.com/jamescalam/2123ce0bb8a871f48a151a023a7ece67\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:47 Creating the Vector DB\n08:56 Implementing Retrieval", "Category": "Science & Technology", "Like Count": 19.0, "Dislike Count": 0.0}
{"Video ID": "lYDiSCDcxmc", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #3 - Make Apps Fast with Caching", "Time Created": "2022-01-27 13:13:14 UTC", "Time Published": "2022-01-27 15:00:36 UTC", "Duration": "584 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 4:\nhttps://www.youtube.com/watch?v=XdxeKiY2UXg&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=4\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:35 Streamlit Caching\n06:56 Experimental Caching Primitives", "Category": "Science & Technology", "Like Count": 24.0, "Dislike Count": 0.0}
{"Video ID": "XdxeKiY2UXg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #4 - Adding Bootstrap Components", "Time Created": "2022-01-28 10:05:43 UTC", "Time Published": "2022-01-28 15:11:42 UTC", "Duration": "590 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.1:\nhttps://www.youtube.com/watch?v=SGazDb8o-to&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=5\n\nStreamlit has proven itself as an incredibly popular tool for quickly putting together high-quality ML-oriented web apps. More recently, it has seen wider adoption in production environments by ever-larger organizations.\n\nAll of this means that there is no better time to pick up some experience with Streamlit. Fortunately, the basics of Streamlit are incredibly easy to learn, and for most tools, this will be more than you need!\n\nIn this series, we will introduce Streamlit by building a general knowledge Q&A interface. We will learn about key Streamlit components like write, text_input, container. How to use external libraries like Bootstrap to quickly create new app components. And use caching to speed up our app.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nhttps://towardsdatascience.com/getting-started-with-streamlit-for-nlp-75fe463821ec?sk=ac5e0b7c39938f52162862411a66a58b\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:35 Streamlit Caching\n06:56 Experimental Caching Primitives", "Category": "Science & Technology", "Like Count": 38.0, "Dislike Count": 1.0}
{"Video ID": "JydpRavoJqI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Adding New Doc Stores to Haystack", "Time Created": "2022-02-15 04:56:36 UTC", "Time Published": "2022-03-15 15:00:14 UTC", "Duration": "1825 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:15 Contributing or Testing\n03:31 ODQA\n06:20 What is Haystack?\n08:13 Haystack QA Workflow\n14:52 Contributing to Open Source\n22:54 Haystack Doc Stores\n26:09 Doc Store Core Methods\n29:31 Final Notes, Contribute/Test", "Category": "Science & Technology", "Like Count": 14.0, "Dislike Count": 0.0}
{"Video ID": "SGazDb8o-to", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.1 - Custom React Components in Streamlit Setup", "Time Created": "2022-02-17 15:24:47 UTC", "Time Published": "2022-02-17 15:45:58 UTC", "Duration": "1158 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.2:\nhttps://www.youtube.com/watch?v=mxm8ihWoVbk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=6\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:19 Environment Setup\n03:42 Starting with a Template\n07:41 Naming for Card Component\n11:31 Installing Node Packages\n15:12 Running the Component", "Category": "Science & Technology", "Like Count": 26.0, "Dislike Count": 1.0}
{"Video ID": "mxm8ihWoVbk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.2 - MUI Card Component Build", "Time Created": "2022-02-20 15:25:56 UTC", "Time Published": "2022-02-21 14:00:31 UTC", "Duration": "1619 seconds", "Description": "\u25b6\ufe0f Streamlit for ML Part 5.3:\nhttps://www.youtube.com/watch?v=lZ2EaPUnV7k&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=7\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:59 Clearing Card Component\n04:59 Building the Component\n14:22 Pulling in MUI Code\n24:08 Adding Roboto Font\n26:05 Final Points", "Category": "Science & Technology", "Like Count": 16.0, "Dislike Count": 1.0}
{"Video ID": "lZ2EaPUnV7k", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Streamlit for ML #5.3 - Publishing Components to Pip", "Time Created": "2022-02-27 16:28:49 UTC", "Time Published": "2022-02-28 17:00:29 UTC", "Duration": "858 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nThere are plenty of prebuilt components designed by Streamlit themselves, and if you can't find what you need, there are even community-built components.\n\nIf you're still stuck, and there is just no component that covers what you need, we can build our own custom components.\n\nTo do this we do need to start playing with the lower-level web technologies that Streamlit itself is built upon. So it isn't as simple as using a prebuilt component. However, thanks to pre-made templates, it isn't too hard to create a new component.\n\nIn this sub-series, we'll learn exactly how to create custom components. We'll focus on designing an interactive card component using Material UI design elements.\n\n\u2757 Python Packaging Video:\nhttps://youtu.be/JkeNVaiUq_c\n\n\u25b6\ufe0f Streamlit for ML Playlist:\nhttps://www.youtube.com/watch?v=JLKUV-LiXjk&list=PLIUOU7oqGTLg5ssYxPGWaci6695wtosGw&index=1\n\n\ud83d\udcd5 Article:\nComing soon\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udcd6 Friend link to article:\nComing soon\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:09 PyPI\n02:41 Preparing for Distribution\n05:43 Build React Component\n06:39 Create Python Package\n11:57 Pip Install\n13:58 Ending", "Category": "Science & Technology", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "J0cntjLKpmU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Train Sentence Transformers by Generating Queries (GenQ)", "Time Created": "2022-03-08 03:10:28 UTC", "Time Published": "2022-03-08 14:52:23 UTC", "Duration": "1634 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nFine-tuning effective dense retrieval models is challenging. Bi-encoders (sentence transformers) are the current best models for dense retrieval in semantic search. Unfortunately, they're also notoriously data-hungry models that typically require a particular type of labeled training data.\n\nHard problems like this attract attention. As expected, there is plenty of attention on building ever better techniques for training retrievers.\n\nOne of the most impressive is GenQ. This approach to building bi-encoder retrievers uses the latest text generation techniques to synthetically generate training data. In short, all we need are passages of text. The generation model then augments these passages with synthetic queries, giving us the exact format we need to train an effective bi-encoder model.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/genq/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:32 Why GenQ?\n02:23 GenQ Overview\n04:28 Training Data\n06:48 Asymmetric Semantic Search\n07:54 T5 Query Generation\n13:52 Finetuning Bi-encoders\n16:02 GenQ Code Walkthrough\n21:40 Finetuning Bi-encoder Walkthrough\n26:48 Final Points", "Category": "Science & Technology", "Like Count": 39.0, "Dislike Count": 0.0}
{"Video ID": "Dn8OYkatiU0", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Testing the New Haystack Doc Store", "Time Created": "2022-03-22 17:15:10 UTC", "Time Published": "2022-03-22 19:26:00 UTC", "Duration": "1399 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:19 Demo Start and Install\n03:25 Initialization\n06:30 Download and Write Documents\n10:55 Extractive QA Pipeline\n11:23 Fetch by ID\n19:01 Metadata Filtering\n22:24 Get All Documents", "Category": "Science & Technology", "Like Count": 5.0, "Dislike Count": 0.0}
{"Video ID": "uEbCXwInnPs", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Is GPL the Future of Sentence Transformers? | Generative Pseudo-Labeling Deep Dive", "Time Created": "2022-03-29 10:46:39 UTC", "Time Published": "2022-03-30 12:52:39 UTC", "Duration": "3175 seconds", "Description": "\ud83c\udf81 Free NLP for Semantic Search Course:\nhttps://www.pinecone.io/learn/nlp\n\nTraining sentence transformers is hard; they need vast amounts of labeled data. On one hand, the internet is full of data, and, on the other, this data is *not* in the format we need. We usually need to use a supervised training method to train a high-performance bi-encoder (sentence transformer) model.\n\nThere is research producing techniques placing us ever closer to fine-tuning high-perfomance bi-encoder models with unlabeled text data. One of the most promising is GPL. At its core, GPL allows us to take unstructured text data and use it to build models that can understand this text. These models can then intelligently respond to natural language queries regarding this same text data.\n\nIt is a fascinating approach, with massive potential across innumerous use cases spanning all industries and borders. With that in mind, let's dive into the details of GPL and how we can implement it to build high-performance LMs with nothing more than plain text.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/gpl/\n\n\ud83d\udd17 Notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/nlp_course/gpl\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:08 Semantic Web and Other Uses\n04:36 Why GPL?\n07:31 How GPL Works\n10:37 Query Generation\n12:08 CORD-19 Dataset and Download\n13:27 Query Generation Code\n21:53 Query Generation is Not Perfect\n22:39 Negative Mining\n26:28 Negative Mining Implementation\n27:21 Negative Mining Code\n35:19 Pseudo-Labeling\n35:55 Pseudo-Labeling Code\n37:01 Importance of Pseudo-Labeling\n41:20 Margin MSE Loss\n43:40 MarginMSE Fine-tune Code\n46:30 Choosing Number of Steps\n48:54 Fast Evaluation\n51:43 What's Next for Sentence Transformers?", "Category": "Science & Technology", "Like Count": 76.0, "Dislike Count": 2.0}
{"Video ID": "j3psNM5y-eA", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Implementing Filters in the New Haystack Doc Store", "Time Created": "2022-04-06 15:53:46 UTC", "Time Published": "2022-04-06 16:26:54 UTC", "Duration": "1695 seconds", "Description": "\ud83e\udd73  Released with Haystack v1.3! Install direct from PyPI with:\n\npip install 'farm-haystack[pinecone]'\n\nJoin me as I work through the final few PR issues on the latest Haystack document store, and figure out how Haystack's filter_utils work.\n\nPR:\nhttps://github.com/deepset-ai/haystack/pull/2254\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:41 Filtering\n05:36 Testing Existing Filter Utils\n07:57 Making Sense of Filter Utils\n10:35 Writing the First Filter\n16:26 First Working Filter\n18:24 Testing New Filters\n21:27 Implementing in the Doc Store\n24:02 Testing Pipeline Filters\n27:11 Final Issue and Outro", "Category": "Science & Technology", "Like Count": 3.0, "Dislike Count": 0.0}
{"Video ID": "ok0SDdXdat8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Spotify's Podcast Search Explained", "Time Created": "2022-04-13 15:02:31 UTC", "Time Published": "2022-04-14 13:14:50 UTC", "Duration": "2998 seconds", "Description": "The market for podcasts has grown tremendously in recent years.\n\nDriving the charge in podcast adoption is Spotify. In a few short years, they have become the undisputed leaders in podcasting. Despite only entering the game in 2018, by late 2021, Spotify had already usurped Apple, the long-reigning leader in podcasts, with more than 28M monthly podcast listeners.\n\nTo back their podcast investments, Spotify has worked on making the podcast experience as seamless and accessible as possible. From their all-in-one podcast creation app (Anchor) to podcast APIs and their latest natural language enabled podcast search.\n\nSpotify\u2019s natural language search for podcasts is a fascinating use case. In the past, users had to rely on keyword/term matching to find the podcast episodes they wanted. Now, they can search in natural language, in much the same way we might ask a real person where to find something.\n\nIn this video, we will take a look under the hood of Spotify's podcast search, and learn how to implement a similar system ourselves.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/spotify-podcast-search\n\n\ud83d\udd17 Code and tests:\nhttps://github.com/pinecone-io/examples/tree/spotify-podcast-search/learn/search-in-wild/spotify-podcast-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:16 NLP in Semantic Search\n08:35 Why Now?\n09:29 Transformer Models\n11:52 Sentence Transformers\n13:12 Vector Search\n15:56 How Spotify Built Podcast Search\n17:35 Data Source, Fine-tuning, and Eval\n22:58 Code Implementation, Dataset\n24:44 Data Preparation\n26:39 Query Generation\n29:54 Fine-tuning a Podcast Model\n41:40 Evaluation\n48:05 Does it Scale?\n49:00 Sharing Your Work", "Category": "Science & Technology", "Like Count": 58.0, "Dislike Count": 1.0}
{"Video ID": "gVAJ_l_S7uQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to learn NLP for free", "Time Created": "2022-04-24 16:41:28 UTC", "Time Published": "2022-04-26 13:05:48 UTC", "Duration": "1402 seconds", "Description": "Knowing what to learn is one of the hardest parts about self-learning. Imagine being thrown into the wilderness and being told to find a specific landmark. Without a map you will end up wandering to wilderness with no better option than taking one step after another.\n\nI spent a long time wandering step-by-step and eventually found my way into working with deep learning and NLP full-time.\n\nHere I will share many of the resources I used or wish I had used in the past. You can this \"curriculum\" as a rough guideline in self-learning ML and working towards a full-time position.\n\nALL LINKS in article/friend link below:\n\n\ud83d\udcd5 Medium article:\nhttps://jamescalam.medium.com/the-self-taught-nlp-engineer-curriculum-c425c3fc3ff6\n\n\ud83d\udcd6 Friend link:\nhttps://jamescalam.medium.com/the-self-taught-nlp-engineer-curriculum-c425c3fc3ff6?sk=986263c644d9b36699d800713faa478a\n\n---\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:53 ML 101 + Prerequisites\n04:58 Sentdex + Neural Nets from Scratch\n07:32 ML Coursera\n09:31 100 Page ML Book\n11:14 Applied ML + Daniel Bourke\n13:17 Origin of Modern NLP\n13:41 CS224N\n14:44 NLP Specialization Coursera\n15:57 Modern NLP + Transformers Intro\n16:54 Transformer Courses\n18:14 Doing Projects\n19:18 Semantic + Vector Search\n19:54 NLP for Semantic Search\n20:44 Mining of Massive Datasets\n22:27 Final Points", "Category": "Science & Technology", "Like Count": 165.0, "Dislike Count": 1.0}
{"Video ID": "fb7LENb9eag", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "BERTopic Explained", "Time Created": "2022-05-10 14:13:06 UTC", "Time Published": "2022-05-11 15:10:23 UTC", "Duration": "2714 seconds", "Description": "90% of the world's data is unstructured. It is built by humans, for humans. That's great for human consumption, but it is *very* hard to organize when we begin dealing with the massive amounts of data abundant in today's information age.\n\nOrganization is complicated because unstructured text data is not intended to be understood by machines, and having humans process this abundance of data is wildly expensive and *very slow*.\n\nFortunately, there is light at the end of the tunnel. More and more of this unstructured text is becoming accessible and understood by machines. We can now search text based on *meaning*, identify the sentiment of text, extract entities, and much more.\n\nTransformers are behind much of this. These transformers are (unfortunately) not Michael Bay's Autobots and Decepticons and (fortunately) not buzzing electrical boxes. Our NLP transformers lie somewhere in the middle, they're not sentient Autobots (yet), but they can understand language in a way that existed only in sci-fi until a short few years ago.\n\nMachines with a human-like comprehension of language are pretty helpful for organizing masses of unstructured text data. In machine learning, we refer to this task as *topic modeling*, the automatic clustering of data into particular topics.\n\nBERTopic takes advantage of the superior language capabilities of these (not yet sentient) transformer models and uses some other ML magic like UMAP and HDBSCAN (more on these later) to produce what is one of the most advanced techniques in language topic modeling today.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/bertopic\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/algos-and-libraries/bertopic\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:40 In this video\n02:58 BERTopic Getting Started\n08:48 BERTopic Components\n15:21 Transformer Embedding\n18:33 Dimensionality Reduction\n25:07 UMAP\n31:48 Clustering\n37:22 c-TF-IDF\n40:49 Custom BERTopic\n44:04 Final Thoughts", "Category": "Science & Technology", "Like Count": 153.0, "Dislike Count": 3.0}
{"Video ID": "O9lrWt15wH8", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Long Form Question Answering (LFQA) in Haystack", "Time Created": "2022-05-17 15:22:17 UTC", "Time Published": "2022-05-17 15:46:21 UTC", "Duration": "2159 seconds", "Description": "Question-Answering (QA) has exploded as a subdomain of Natural Language Processing (NLP) in the last few years. QA is a widely applicable use case in NLP yet was out of reach until the introduction of [transformer models](/learn/transformers/) in 2017.\n\nWithout transformer models, the level of language comprehension required to make something as complex as QA work simply was not possible.\n\nAlthough QA is a complex topic, it comes from a simple idea. The automatic retrieval of information via a more human-like interaction. The task of information retrieval (IR) is performed by almost every organization in the world. Without other options, organizations rely on person-to-person IR and rigid keyword search tools. This haphazard approach to IR generates a lot of friction, particularly for larger organizations.\n\nQA offers a solution to this problem. Rather than these documents being lost in an abyss, they can be stored within a space where an intelligent QA agent can access them. Unlike humans, our QA agent can scan millions of documents in seconds and return answers from these documents almost instantly.\n\nWith QA tools, employees can stop wasting time searching for snippets of information and focus on their *real*, value-adding tasks.\n\nA small investment in QA is, for most organizations, a no-brainer.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/haystack-lfqa\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/blob/master/integrations/haystack/haystack_lfqa.ipynb\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:20 Approaches to Question Answering\n05:43 Components of QA Pipeline\n08:58 LFQA Generator\n09:40 Haystack Setup\n10:32 Initialize Document Store\n13:02 Getting Data\n17:53 Indexing Embeddings\n21:51 Initialize Generator\n24:10 Asking Questions\n26:12 Common Problems\n29:32 Generator Memory\n31:30 Few More Questions\n34:54 Outro", "Category": "Science & Technology", "Like Count": 55.0, "Dislike Count": 1.0}
{"Video ID": "uYas6ysyjgY", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "New GPU-Acceleration for PyTorch on M1 Macs! + using with BERT", "Time Created": "2022-05-22 16:37:37 UTC", "Time Published": "2022-05-24 13:00:34 UTC", "Duration": "1140 seconds", "Description": "GPU-acceleration on Mac is finally here!\n\nToday's deep learning models owe a great deal of their exponential performance gains to ever increasing model sizes. Those larger models require more computations to train and run.\n\nThese models are simply too big to be run on CPU hardware, which performs large step-by-step computations. Instead, they need massively parallel computations. That leaves us with either GPU or TPU hardware.\n\nOur home PCs aren't coming with TPUs anytime soon, so we're left with the GPU option. GPUs use a highly parallel structure, originally designed to process images for visual heavy processes. They became essential components in gaming for rendering real-time 3D images.\n\nGPUs are essential for the scale of today's models. Using CPUs makes many of these models too slow to be useful, which can make deep learning on M1 machines rather disappointing.\n\nFortunately, this is changing with the support of GPU on M1 machines beginning with PyTorch v1.12. In this video we will explain the new integration and how to implement it yourself.\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/gpu-acceleration-comes-to-pytorch-on-m1-macs-195c399efcc1\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/gpu-acceleration-comes-to-pytorch-on-m1-macs-195c399efcc1?sk=a88acd35f600858093c177b97d690b03\n\n\ud83d\udd17  Code notebooks:\nhttps://github.com/jamescalam/pytorch-mps\n\n\ud83e\udd16  70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89  Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e  Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:34 PyTorch MPS\n04:57 Installing ARM Python\n09:09 Using PyTorch with GPU\n12:14 BERT on PyTorch GPU\n13:51 Best way to train LLMs on Mac\n16:01 Buffer Size Bug\n17:24 When we would use Mac M1 GPU", "Category": "Science & Technology", "Like Count": 115.0, "Dislike Count": 3.0}
{"Video ID": "FzLIIwiaXSU", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Build an AI-Powered Video Search App", "Time Created": "2022-06-01 12:37:21 UTC", "Time Published": "2022-06-01 16:29:43 UTC", "Duration": "1343 seconds", "Description": "Technology and culture have advanced and become ever more entangled. Some of the most significant technological breakthroughs are integrated so tightly into our culture that we never even notice they\u2019re there.\n\nOne of those is AI-powered search. It powers your Google results, Netflix recommendations, and ads you see everywhere. It is being rapidly weaved throughout all aspects of our lives. Further, this is a new technology; its full potential is unknown.\n\nThis technology weaves directly into the cultural phenomenon of YouTube. Imagine a search engine like Google that allows you to rapidly access the billions of hours of YouTube content. There is no comparison to that level of highly engaging video content in the world.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/youtube-search\n\n\ud83d\udd17 Code:\nhttps://github.com/pinecone-io/examples/tree/master/learn/projects/yt-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n02:56 YouTube Search App\n04:43 Getting Data\n07:58 Enhancing the Data\n12:45 Scraping Other Metadata\n14:52 Loading Data from Hugging Face\n15:42 Index and Query the Data\n20:43 Streamlit App Code", "Category": "Science & Technology", "Like Count": 58.0, "Dislike Count": 0.0}
{"Video ID": "xXsDIK9z_fg", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Using Semantic Search to Find GIFs", "Time Created": "2022-06-06 09:17:01 UTC", "Time Published": "2022-06-07 12:05:40 UTC", "Duration": "1050 seconds", "Description": "Vector search powers some of the most popular services in the world. It serves your Google results, delivers the best podcasts on Spotify, and accounts for at least 35% of consumer purchases on Amazon.\n\nIn this article, we will use vector search applied to language, called semantic search, to build a GIF search engine. Unlike more traditional search where we rely on keyword matching, semantic search enables search based on the human meaning behind text and images. That means we can find highly relevant GIFs with natural language prompts.\n\nThe pipeline for a project like this is simple, yet powerful. It can easily be adapted to tasks as diverse as video search or answering Super Bowl questions, or as we\u2019ll see, finding GIFs.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/gif-search\n\n\ud83d\udd17 Code:\nhttps://github.com/pinecone-io/examples/tree/master/learn/projects/gif-search\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:17 GIF Search Demo\n01:56 Pipeline Overview\n05:33 Data Preparation\n08:17 Vector Database and Retriever\n12:37 Querying\n15:42 Streamlit App Code", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 1.0}
{"Video ID": "_OAU1kQdmgE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to Learn Data Science | ML | Programming", "Time Created": "2022-06-15 10:37:57 UTC", "Time Published": "2022-06-15 13:11:47 UTC", "Duration": "992 seconds", "Description": "In this video I share five of the approaches/thoughts I have regarding learning, in particular for learning data science, machine learning, or programming.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:33 Scale of Theory vs. Applied\n02:55 Shape of Learning\n05:52 Courses vs. Projects\n08:37 Open Source\n10:44 Writing\n12:44 Following Interests\n15:42 Final Notes", "Category": "Education", "Like Count": 24.0, "Dislike Count": 0.0}
{"Video ID": "BD9TkvEsKwM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Evaluation Measures for Search and Recommender Systems", "Time Created": "2022-06-25 14:35:27 UTC", "Time Published": "2022-06-28 15:06:40 UTC", "Duration": "1885 seconds", "Description": "In this video you will learn about popular offline metrics (evaluation measures) like Recall@K, Mean Reciprocal Rank (MRR), Mean Average Precision@K (MAP@K), and Normalized Discounted Cumulative Gain (NDCG@K). We will also demonstrate how each of these metrics can be replicated in Python.\n\nEvaluation of information retrieval (IR) systems is critical to making well-informed design decisions. From search to recommendations, evaluation measures are paramount to understanding what does and does not work in retrieval.\n\nMany big tech companies contribute much of their success to well-built IR systems. One of Amazon\u2019s earliest iterations of the technology was reportedly driving more than 35% of their sales. Google attributes 70% of YouTube views to their IR recommender systems.\n\nIR systems power some of the greatest companies in the world, and behind every successful IR system is a set of evaluation measures.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/offline-evaluation\n\n\ud83d\udd17 Code notebooks:\nhttps://github.com/pinecone-io/examples/tree/master/learn/algos-and-libraries/offline-evaluation\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:51 Offline Metrics\n02:38 Dataset and Retrieval 101\n06:08 Recall@K\n07:57 Recall@K in Python\n09:03 Disadvantages of Recall@K\n10:21 MRR\n13:32 MRR in Python\n14:18 MAP@K\n18:17 MAP@K in Python\n19:27 NDCG@K\n29:26 Pros and Cons of NDCG@K\n29:48 Final Thoughts", "Category": "Science & Technology", "Like Count": 48.0, "Dislike Count": 0.0}
{"Video ID": "coaaSxys5so", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to build next-level Q&A with OpenAI", "Time Created": "2022-07-06 19:48:54 UTC", "Time Published": "2022-07-07 13:24:35 UTC", "Duration": "1168 seconds", "Description": "Walkthrough of the OpenAI x Pinecone Q&A app I built for a webinar with OpenAI. This is the coolest Q&A app I've ever built thanks to Pinecone vector search and OpenAI's incredible embeddings and generation endpoints.\n\nLINKS:\n\ud83d\udd79 App:\nhttps://pinecone-io-playground-beyond-search-openaisrcserver-h65vzl.streamlitapp.com\n\ud83d\udc68\u200d\ud83d\udcbb Code and Data:\nhttps://github.com/pinecone-io/examples/tree/master/integrations/openai/beyond_search_webinar\nOpenAI x Pinecone Webinar:\n\u25b6\ufe0f https://www.youtube.com/watch?v=HtI9easWtAA\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 36.0, "Dislike Count": 0.0}
{"Video ID": "I3na13AESjw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How to use Color Histograms for Image Retrieval", "Time Created": "2022-07-11 07:01:31 UTC", "Time Published": "2022-07-13 16:22:08 UTC", "Duration": "1864 seconds", "Description": "Browsing, searching, and retrieving images has never been easy. Traditionally, many technologies relied on manually appending metadata to images and searching via this metadata. This approach works for datasets with high-quality annotation, but most datasets are too large for manual annotation.\n\nThat means any large image dataset must rely on Content-Based Image Retrieval (CBIR). Search with CBIR focuses on comparing the *content* of an image rather than its metadata. Content can be color, shapes, textures \u2013 or with some of the latest advances in ML \u2014 the \"human meaning\" behind an image.\n\nColor histograms represent one of the first CBIR techniques, allowing us to search through images based on their color profiles rather than metadata.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/color-histograms\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:23 What are Color Histograms?\n08:39 How to Built Color Histograms\n16:56 Using OpenCV calcHist\n20:36 Image Retrieval\n27:37 Pros and Cons\n30:40 Final Points", "Category": "Science & Technology", "Like Count": 23.0, "Dislike Count": 0.0}
{"Video ID": "UzkdOg7wWmI", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "\ud83e\udd17 Hugging Face just released *Diffusers* - for models like DALL-E 2 and Imagen!", "Time Created": "2022-07-23 21:33:08 UTC", "Time Published": "2022-07-26 15:27:46 UTC", "Duration": "934 seconds", "Description": "Hugging Face of transformer fame have created a whole new Python library for diffusion models! Diffusion models are a key component of models like OpenAI's DALL-E-2, Google's Imagen, and Midjourney's image generation service. HuggingFace Diffusers brings these models to a new level of accessibility (and open source!).\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/hugging-face-just-released-the-diffusers-library-846f32845e65\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/hugging-face-just-released-the-diffusers-library-846f32845e65?sk=9ec4027460defa1fd25178af9a55da13\n\n\ud83e\udde8 Diffusers:\nhttps://github.com/huggingface/diffusers\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n00:00 What are Diffusers?\n01:55 Getting started\n04:20 Prompt engineering\n09:34 Testing other diffusers", "Category": "Science & Technology", "Like Count": 61.0, "Dislike Count": 0.0}
{"Video ID": "szfG55juoJE", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "How I work from anywhere", "Time Created": "2022-07-24 14:01:51 UTC", "Time Published": "2022-08-16 13:55:16 UTC", "Duration": "767 seconds", "Description": "Overview of how I deal with travel and work. Remote desk setup for staying as ergonomic and productive as possible, enjoy!\n\n\ud83d\udd17 Links to products (mostly affiliate):\nLaptop stand: https://amzn.to/3bZqMHM\nSecond screen: https://amzn.to/3w6IT5B\nCable bag (international): https://amzn.to/3QBH7S7\n                              ... or UK: https://amzn.to/3ps5lT2\nPeak Design backpacks: https://www.peakdesign.com/products/everyday-backpack\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 32.0, "Dislike Count": 1.0}
{"Video ID": "jjQetJtQDS4", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Bag of *Visual* Words for Image Classification and Retrieval", "Time Created": "2022-08-02 20:39:30 UTC", "Time Published": "2022-08-03 13:00:35 UTC", "Duration": "3367 seconds", "Description": "In computer vision, bag of visual words (BoVW) is one of the pre-deep learning models used for building image embeddings. Allowing us to retrieve images from a database that are similar to another \"query\" image, perform object detection, and image classification.\n\n\ud83c\udf32 Pinecone article:\nhttps://www.pinecone.io/learn/bag-of-visual-words/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 33.0, "Dislike Count": 0.0}
{"Video ID": "989aKUVBfbk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Fast intro to multi-modal ML with OpenAI's CLIP", "Time Created": "2022-08-11 06:17:14 UTC", "Time Published": "2022-08-11 13:03:08 UTC", "Duration": "1374 seconds", "Description": "OpenAI's CLIP is \"multi-modal\" model capable of understanding the relationships and concepts between both text and images. As we'll see, CLIP is very capable, and when used via the Hugging Face library, could not be easier to work with.\n\n\ud83d\udcd5  Article:\nhttps://towardsdatascience.com/quick-fire-guide-to-multi-modal-ml-with-openais-clip-2dad7e398ac0\n\n\ud83d\udcd6  Friend Link (free access):\nhttps://towardsdatascience.com/quick-fire-guide-to-multi-modal-ml-with-openais-clip-2dad7e398ac0?sk=89bb2d8b8e583ed109d8a05e00366645\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:15 What is CLIP?\n02:13 Getting started\n05:38 Creating text embeddings\n07:23 Creating image embeddings\n10:26 Embedding a lot of images\n15:08 Text-image similarity search\n21:38 Alternative image and text search", "Category": "Science & Technology", "Like Count": 31.0, "Dislike Count": 0.0}
{"Video ID": "c_u4AHNjOpk", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "AlexNet and ImageNet Explained", "Time Created": "2022-08-23 22:13:25 UTC", "Time Published": "2022-08-24 13:00:22 UTC", "Duration": "2180 seconds", "Description": "Today\u2019s deep learning revolution traces back to the 30th of September, 2012. On this day, a Convolutional Neural Network (CNN) called AlexNet won the ImageNet 2012 challenge. AlexNet didn\u2019t just win; it dominated.\n\nAlexNet was unlike the other competitors. This new model demonstrated unparalleled performance on the largest image dataset of the time, ImageNet. This event made AlexNet the first widely acknowledged, successful application of deep learning. It caught people\u2019s attention with a 9.8 percentage point advantage over the nearest competitor.\n\nUntil this point, deep learning was a nice idea that most deemed as impractical. AlexNet showed that deep learning was more than a pipedream, and the authors showed the world how to make it practical. Yet, the surge of deep learning that followed was not fueled solely by AlexNet. Indeed, without the huge ImageNet dataset, there would have been no AlexNet.\n\nThe future of AI was to be built on the foundations set by the ImageNet challenge and the novel solutions that enabled the synergy between ImageNet and AlexNet.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/imagenet\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:06 Birth of Deep Learning\n02:52 ImageNet\n07:56 Lack of Readiness for Big Datasets\n09:57 ImageNet Challenge (ILSVRC)\n11:47 AlexNet\n19:30 PYTORCH IMPLEMENTATION\n19:55 Data Preprocessing\n27:06 Class Prediction with AlexNet\n31:50 Goldfish Results\n34:27 Closing Notes", "Category": "Science & Technology", "Like Count": 20.0, "Dislike Count": 0.0}
{"Video ID": "pfwBut7E60Q", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Ultra-efficient Classifier Fine-tuning with Vector Search", "Time Created": "2022-08-31 00:32:14 UTC", "Time Published": "2022-08-31 13:00:26 UTC", "Duration": "1932 seconds", "Description": "Learn how to use vector search to create highly targeted training for any classification model using a final linear classification layer. Easily fine-tune models in 10 minutes with less than 100 labeled examples.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/classifier-train-vector-search/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n01:14 Classification\n02:49 Better Classifier Training\n06:33 Classification as Vector Search\n08:47 How Fine-tuning Works\n10:50 Identifying Important Samples\n12:39 CODE IMPLEMENTATION\n13:13 Indexing\n18:59 Fine-tuning the Classifier\n27:37 Classifier Predictions\n30:43 Closing Notes", "Category": "Science & Technology", "Like Count": 49.0, "Dislike Count": 0.0}
{"Video ID": " -S20nblUuNw", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hugging Face Datasets #1 - Hosting your datasets", "Time Created": "2022-09-09 12:52:32 UTC", "Time Published": "2022-09-09 14:18:34 UTC", "Duration": "1382 seconds", "Description": "Introduction to Hugging Face datasets, how it works, and how to host your own simple datasets (JSONL, TSV, CSV, etc) for free via Hugging Face Datasets Hub\n\nWarp download:\nhttps://app.warp.dev/referral/7G3N39\n\nGit LFS Install:\nMac:\n$ brew install git-lfs\nDebian/Ubuntu:\n$ curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash\n$ sudo apt-get install git-lfs\nWindows:\nGet install from https://github.com/git-lfs/git-lfs/releases\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n04:36 Creating our own Datasets\n08:29 Creating JSONL for Hugging Face\n15:15 Uploading Datasets for Git\n19:10 LFS for Large Files\n21:56 Closing Notes", "Category": "Science & Technology", "Like Count": 14.0, "Dislike Count": 0.0}
{"Video ID": "fGwH2YoQkDM", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "CLIP Explained | Multi-modal ML", "Time Created": "2022-09-14 23:08:40 UTC", "Time Published": "2022-09-15 13:00:22 UTC", "Duration": "2013 seconds", "Description": "Language models (LMs) can not rely on language alone. That is the idea behind the \"Experience Grounds Language\" paper, that proposes a framework to measure LMs' current and future progress. A key idea is that, beyond a certain threshold LMs need other forms of data, such as visual input.\n\nThe next step beyond well-known language models; BERT, GPT-3, and T5 is \u201dWorld Scope 3\u201d. In World Scope 3, we move from large text-only datasets to large multi-modal datasets. That is, datasets containing information from multiple forms of media, like *both* images and text.\n\nThe world, both digital and real, is multi-modal. We perceive the world as an orchestra of language, imagery, video, smell, touch, and more. This chaotic ensemble produces an inner state, our \"model\" of the outside world.\n\nAI must move in the same direction. Even specialist models that focus on language or vision must, at some point, have input from the other modalities. How can a model fully understand the concept of the word \"person\" without *seeing* a person?\n\nOpenAI's Contrastive Learning In Pretraining (CLIP) is a world scope three model. It can comprehend concepts in both text and image and even connect concepts between the two modalities. In this video we will learn about multi-modality, how CLIP works, and how to use CLIP for different use cases like encoding, classification, and object detection.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/clip/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 50.0, "Dislike Count": 1.0}
{"Video ID": "ODdKC30dT8c", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Hugging Face Datasets #2 - Dataset Builder Scripts", "Time Created": "2022-09-23 14:06:51 UTC", "Time Published": "2022-09-23 14:45:22 UTC", "Duration": "1404 seconds", "Description": "How to work with dataset builder scripts, intro to the download manager, and Apache Arrow datatypes used in Hugging Face Datasets.\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP\n\n00:00 Intro\n00:49 Creating Compressed Files\n02:41 Creating Dataset Build Script\n04:49 Download Manager\n08:59 Finishing Split Generator\n10:13 Generate Examples Method\n14:47 Add Dataset to Hugging Face\n17:49 Apache Arrow Features\n22:52 What's Next?", "Category": "Science & Technology", "Like Count": 13.0, "Dislike Count": 0.0}
{"Video ID": "98POYg2HZqQ", "Channel ID": "UCv83tO5cePwHMt1952IVVHw", "Title": "Zero-Shot Image Classification with OpenAI's CLIP", "Time Created": "2022-10-04 05:29:02 UTC", "Time Published": "2022-10-05 14:00:03 UTC", "Duration": "1303 seconds", "Description": "State-of-the-art (SotA) computer vision (CV) models are characterized by a *restricted* understanding of the visual world specific to their training data [1].\n\nThese models can perform *very well* on specific tasks and datasets, but they do not generalize well. They cannot handle new classes or images beyond the domain they have been trained with.\n\nIdeally, a CV model should learn the contents of images without excessive focus on the specific labels it is initially trained to understand.\n\nFortunately, OpenAI's CLIP has proved itself as an incredibly flexible CV classification model that often requires *zero* retraining. In this chapter, we will explore CLIP in zero-shot image classification.\n\n\ud83c\udf32 Pinecone article:\nhttps://pinecone.io/learn/clip-classification/\n\n\ud83e\udd16 70% Discount on the NLP With Transformers in Python course:\nhttps://bit.ly/3DFvvY5\n\n\ud83c\udf89 Subscribe for Article and Video Updates!\nhttps://jamescalam.medium.com/subscribe\nhttps://medium.com/@jamescalam/membership\n\n\ud83d\udc7e Discord:\nhttps://discord.gg/c5QtDB9RAP", "Category": "Science & Technology", "Like Count": 10.0, "Dislike Count": 0.0}
{"Video ID": "efPrtcLdcdM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "This is the worst AI ever", "Time Created": null, "Time Published": "2022-06-03T15:25:58Z", "Duration": null, "Description": "gpt4chan #4chan #ai GPT-4chan was trained on over 3 years of posts from 4chan's \"politically incorrect\" (/pol/) board. (and no ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TrdevFK_am4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (Paper Explained)", "Time Created": null, "Time Published": "2020-10-04T11:22:34Z", "Duration": null, "Description": "ai #research #transformers Transformers are Ruining Convolutions. This paper, under review at ICLR, shows that given enough ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6MUpWGeGMxs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeuralHash is BROKEN - How to evade Apple's detection & craft hash collisions (w/ Open Source Code)", "Time Created": null, "Time Published": "2021-08-19T14:03:52Z", "Duration": null, "Description": "apple #icloud #neuralhash Send your Apple fanboy friends to prison with this one simple trick ;) We break Apple's NeuralHash ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "n622girLRNM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Microsoft combines Images & Text | Meta makes artificial skin | Russians replicate DALL-E", "Time Created": null, "Time Published": "2021-11-12T09:29:59Z", "Duration": null, "Description": "mlnews #turing #reskin The latest and greatest from the Machine Learning world OUTLINE: 0:00 - Intro 0:15 - Sponsor: Weights ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "W3mrgqtm5R4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] BLOOM: 176B Open-Source | Chinese Brain-Scale Computer | Meta AI: No Language Left Behind", "Time Created": null, "Time Published": "2022-07-27T20:22:22Z", "Duration": null, "Description": "mlnews #bloom #ai Today we look at all the recent giant language models in the AI world! OUTLINE: 0:00 - Intro 0:55 - BLOOM: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iDulhoQ2pro", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Attention Is All You Need", "Time Created": null, "Time Published": "2017-11-28T08:04:38Z", "Duration": null, "Description": "https://arxiv.org/abs/1706.03762 Abstract: The dominant sequence transduction models are based on complex recurrent or ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TrLrBL1U8z0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] GitHub Copilot - Copyright, GPL, Patents & more | Brickit LEGO app | Distill goes on break", "Time Created": null, "Time Published": "2021-07-08T12:14:37Z", "Duration": null, "Description": "copilot #copyright #gpl GitHub and OpenAI release Copilot, an AI-powered code autocomplete system that can generate entire ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "P_xeshTnPZg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Perceiver: General Perception with Iterative Attention (Google DeepMind Research Paper Explained)", "Time Created": null, "Time Published": "2021-03-22T17:26:39Z", "Duration": null, "Description": "perceiver #deepmind #transformer Inspired by the fact that biological creatures attend to multiple modalities at the same time, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rl4nUngiR2k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "BLEURT: Learning Robust Metrics for Text Generation (Paper Explained)", "Time Created": null, "Time Published": "2020-06-07T14:11:39Z", "Duration": null, "Description": "Proper evaluation of text generation models, such as machine translation systems, requires expensive and slow human ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "19Q-vMd9bYg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment (Paper Explained)", "Time Created": null, "Time Published": "2021-09-27T13:22:14Z", "Duration": null, "Description": "neurips #peerreview #nips The peer-review system at Machine Learning conferences has come under much criticism over the last ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rHQPBqMULXo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Machine Learning PhD Survival Guide 2021 | Advice on Topic Selection, Papers, Conferences & more!", "Time Created": null, "Time Published": "2021-03-30T14:09:13Z", "Duration": null, "Description": "machinelearning #phd #howto This video is advice for new PhD students in the field of Machine Learning in 2021 and after.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GWt6Fu05voI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Classic] Deep Residual Learning for Image Recognition (Paper Explained)", "Time Created": null, "Time Published": "2020-07-14T13:00:04Z", "Duration": null, "Description": "ai #research #resnet ResNets are one of the cornerstones of modern Computer Vision. Before their invention, people were not ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pH2jZun8MoY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Involution: Inverting the Inherence of Convolution for Visual Recognition (Research Paper Explained)", "Time Created": null, "Time Published": "2021-05-08T10:17:15Z", "Duration": null, "Description": "involution #computervision #attention Convolutional Neural Networks (CNNs) have dominated computer vision for almost a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mIZLGBD99iU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Did Google's LaMDA chatbot just become sentient?", "Time Created": null, "Time Published": "2022-06-15T22:16:05Z", "Duration": null, "Description": "lamda #google #ai Google engineer Blake Lemoine was put on leave after releasing proprietary information: An interview with the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RJwPN4qNi_Y", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Google's 540B PaLM Language Model & OpenAI's DALL-E 2 Text-to-Image Revolution", "Time Created": null, "Time Published": "2022-04-10T09:08:24Z", "Duration": null, "Description": "mlnews #palm #dalle2 Google releases PaLM and OpenAI releases DALL-E 2 (and more news). Sponsor: Weights & BIases Start ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YQ2QtKcK2dA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Man behind Stable Diffusion", "Time Created": null, "Time Published": "2022-08-13T10:52:40Z", "Duration": null, "Description": "stablediffusion #ai #stabilityai An interview with Emad Mostaque, founder of Stability AI. OUTLINE: 0:00 - Intro 1:30 - What is ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CRlN-cYFxTk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ML Research Paper Explained)", "Time Created": null, "Time Published": "2021-04-19T15:21:29Z", "Duration": null, "Description": "nerf #neuralrendering #deeplearning View Synthesis is a tricky problem, especially when only given a sparse set of images as an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_Z9ZP1eiKsI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Curiosity-driven Exploration by Self-supervised Prediction", "Time Created": null, "Time Published": "2018-03-18T12:07:52Z", "Duration": null, "Description": "https://arxiv.org/abs/1705.05363 Authors: Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell Abstract: In many ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a-VQfQqIMrE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "mixup: Beyond Empirical Risk Minimization (Paper Explained)", "Time Created": null, "Time Published": "2020-05-27T14:13:12Z", "Duration": null, "Description": "Neural Networks often draw hard boundaries in high-dimensional space, which makes them very brittle. Mixup is a technique that ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "af6WPqvzjjk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Text-to-Image models are taking over! (Imagen, DALL-E 2, Midjourney, CogView 2 & more)", "Time Created": null, "Time Published": "2022-08-07T12:54:12Z", "Duration": null, "Description": "mlnews #dalle #imagen All things text-to-image models like DALL-E and Imagen! OUTLINE: 0:00 - Intro 0:30 - Imagen: Google's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vLTmnaMpQCs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning to summarize from human feedback (Paper Explained)", "Time Created": null, "Time Published": "2020-09-07T11:56:46Z", "Duration": null, "Description": "summarization #gpt3 #openai Text Summarization is a hard task, both in training and evaluation. Training is usually done ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "We20YSAJZSE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "MuZero: Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model", "Time Created": null, "Time Published": "2019-11-21T12:23:05Z", "Duration": null, "Description": "MuZero harnesses the power of AlphaZero, but without relying on an accurate environment model. This opens up planning-based ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6dvcYx9hcbE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents", "Time Created": null, "Time Published": "2022-03-08T16:24:37Z", "Duration": null, "Description": "deepmind #rl #society This is an in-depth paper review, followed by an interview with the papers' authors! Society is ruled by ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PuOASKpiThY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I'm taking a break", "Time Created": null, "Time Published": "2021-07-11T12:51:06Z", "Duration": null, "Description": "I'll be back, don't worry :) Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OioFONrSETc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift", "Time Created": null, "Time Published": "2019-02-02T15:16:38Z", "Duration": null, "Description": "https://arxiv.org/abs/1502.03167 Abstract: Training Deep Neural Networks is complicated by the fact that the distribution of each ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M2-BE5JotjA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "PAIR AI Explorables | Is the problem in the data? Examples on Fairness, Diversity, and Bias.", "Time Created": null, "Time Published": "2021-04-07T12:38:57Z", "Duration": null, "Description": "In the recurring debate about bias in Machine Learning models, there is a growing argument saying that \"the problem is not in the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7K4Z8RqjWIk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "MLP-Mixer: An all-MLP Architecture for Vision (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-05-06T11:53:49Z", "Duration": null, "Description": "mixer #google #imagenet Convolutional Neural Networks have dominated computer vision for nearly 10 years, and that might ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dND-7llwrpw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)", "Time Created": null, "Time Published": "2021-10-06T20:12:52Z", "Duration": null, "Description": "grokking #openai #deeplearning Grokking is a phenomenon when a neural network suddenly learns a pattern in the dataset and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "T35ba_VXkMY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DETR: End-to-End Object Detection with Transformers (Paper Explained)", "Time Created": null, "Time Published": "2020-05-28T15:09:01Z", "Duration": null, "Description": "Object detection in images is a notoriously hard task! Objects can be of a wide variety of classes, can be numerous or absent, they ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_8KNb5iqblE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Longformer: The Long-Document Transformer", "Time Created": null, "Time Published": "2020-04-20T14:07:56Z", "Duration": null, "Description": "The Longformer extends the Transformer by introducing sliding window attention and sparse global attention. This allows for the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "T9XSU0pKX2E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "OpenAI CLIP: ConnectingText and Images (Paper Explained)", "Time Created": null, "Time Published": "2021-01-12T14:52:03Z", "Duration": null, "Description": "ai #openai #technology Paper Title: Learning Transferable Visual Models From Natural Language Supervision CLIP trains on 400 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "h3ij3F3cPIk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DINO: Emerging Properties in Self-Supervised Vision Transformers (Facebook AI Research Explained)", "Time Created": null, "Time Published": "2021-05-01T19:53:03Z", "Duration": null, "Description": "dino #facebook #selfsupervised Self-Supervised Learning is the final frontier in Representation Learning: Getting useful features ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dmH1ZpcROMk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reward Is Enough (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-05-31T13:27:21Z", "Duration": null, "Description": "reinforcementlearning #deepmind #agi What's the most promising path to creating Artificial General Intelligence (AGI)? This paper ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rFwQDDbYTm4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Classic] Playing Atari with Deep Reinforcement Learning (Paper Explained)", "Time Created": null, "Time Published": "2020-07-26T13:00:23Z", "Duration": null, "Description": "ai #dqn #deepmind After the initial success of deep neural networks, especially convolutional neural networks on supervised ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aX8phGhG8VQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Does GPT-3 lie? - Misinformation and fear-mongering around the TruthfulQA dataset", "Time Created": null, "Time Published": "2021-09-21T13:43:28Z", "Duration": null, "Description": "gpt-3 #truth #conspiracy A new benchmark paper has created quite an uproar in the community. TruthfulQA is a dataset of 817 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Elxn8rS88bI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Pretrained Transformers as Universal Computation Engines (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-03-16T18:15:38Z", "Duration": null, "Description": "universalcomputation #pretrainedtransformers #finetuning Large-scale pre-training and subsequent fine-tuning is a common ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jltgNGt8Lpg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Neural Ordinary Differential Equations", "Time Created": null, "Time Published": "2019-02-19T05:12:20Z", "Duration": null, "Description": "https://arxiv.org/abs/1806.07366 Abstract: We introduce a new family of deep neural network models. Instead of specifying a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eYgPJ_7BkEw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence", "Time Created": null, "Time Published": "2020-04-15T18:01:56Z", "Duration": null, "Description": "FixMatch is a simple, yet surprisingly effective approach to semi-supervised learning. It combines two previous methods in a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DEh1GR0t29k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Peer Review is still BROKEN! The NeurIPS 2021 Review Experiment (results are in)", "Time Created": null, "Time Published": "2021-11-25T18:26:52Z", "Duration": null, "Description": "neurips #peerreview #machinelearning A look at the results of the 2021 NeurIPS peer review experiment.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hsOMCwvFv80", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I'm out of Academia", "Time Created": null, "Time Published": "2021-05-04T13:25:48Z", "Duration": null, "Description": "machinelearning #ai #phd Done with my PhD in Machine Learning at ETH Zurich. On to new lands! Links: TabNine Code ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "VgqHitvEbR0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] REVIEWER #2: How Peer Review is FAILING in Machine Learning", "Time Created": null, "Time Published": "2020-08-18T11:16:07Z", "Duration": null, "Description": "ai #research #peerreview Machine Learning research is in dire straits as more people flood into the field and competent reviewers ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kOy49NqZeqI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures", "Time Created": null, "Time Published": "2019-11-01T13:08:17Z", "Duration": null, "Description": "Policy Gradient RL on a massively distributed scale with theoretical guarantees! Abstract: In this work we aim to solve a large ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xbxe-x6wvRw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Stable Diffusion Takes Over! (Open Source AI Art)", "Time Created": null, "Time Published": "2022-09-19T00:06:24Z", "Duration": null, "Description": "stablediffusion #aiart #mlnews Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0PAiQ1jTN5k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "How to make your CPU as fast as a GPU - Advances in Sparsity w/ Nir Shavit", "Time Created": null, "Time Published": "2022-09-17T12:19:00Z", "Duration": null, "Description": "ai #sparsity #gpu Sparsity is awesome, but only recently has it become possible to properly handle sparse models at good ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rNkHjZtH0RQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NFNets: High-Performance Large-Scale Image Recognition Without Normalization (ML Paper Explained)", "Time Created": null, "Time Published": "2021-02-14T16:51:10Z", "Duration": null, "Description": "nfnets #deepmind #machinelearning Batch Normalization is a core component of modern deep learning. It enables training at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dWGjoInRaAs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind fails to get independence from Google", "Time Created": null, "Time Published": "2021-05-26T20:24:08Z", "Duration": null, "Description": "deepmind #google #mlnews DeepMind has reportedly failed to negotiate for greater independence from Google/Alphabet.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iAR8LkkMMIM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity", "Time Created": null, "Time Published": "2021-01-22T19:38:10Z", "Duration": null, "Description": "ai #technology #switchtransformer Scale is the next frontier for AI. Google Brain uses sparsity and hard routing to massively ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_9aN1-0T8hg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] AI models that write code (Copilot, CodeWhisperer, Pangu-Coder, etc.)", "Time Created": null, "Time Published": "2022-08-10T20:55:14Z", "Duration": null, "Description": "mlnews #ai #copilot OUTLINE: 0:00 - Intro 0:20 - Copilot Now Generally Available 3:20 - FOSS Org leaves GitHub 6:45 - Google's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pwSnC8jlh50", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Meta's OPT 175B language model | DALL-E Mega is training | TorToiSe TTS fakes my voice", "Time Created": null, "Time Published": "2022-05-10T12:54:25Z", "Duration": null, "Description": "mlnews #dalle #gpt3 An inside look of what's happening in the ML world! Sponsor: Weights & Biases https://wandb.me/yannic ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-9evrZnBorM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding", "Time Created": null, "Time Published": "2019-01-30T08:51:15Z", "Duration": null, "Description": "https://arxiv.org/abs/1810.04805 Abstract: We introduce a new language representation model called BERT, which stands for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "awyuuJoHawo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Dream to Control: Learning Behaviors by Latent Imagination", "Time Created": null, "Time Published": "2020-04-03T12:46:59Z", "Duration": null, "Description": "Dreamer is a new RL agent by DeepMind that learns a continuous control task through forward-imagination in latent space.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FNDVy_BR8aA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Can Wikipedia Help Offline Reinforcement Learning? (Author Interview)", "Time Created": null, "Time Published": "2022-02-28T15:24:13Z", "Duration": null, "Description": "wikipedia #reinforcementlearning #languagemodels Original paper review here: https://youtu.be/XHGh19Hbx48 Machel Reid and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DEh1GR0t29k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Peer Review is still BROKEN! The NeurIPS 2021 Review Experiment (results are in)", "Time Created": null, "Time Published": "2021-11-25T18:26:52Z", "Duration": null, "Description": "neurips #peerreview #machinelearning A look at the results of the 2021 NeurIPS peer review experiment.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yPjuAo53uNI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] The Male Only History of Deep Learning", "Time Created": null, "Time Published": "2020-04-22T11:58:28Z", "Duration": null, "Description": "This casting of our field in terms of ideological narrow-sighted group-think is disgusting. Keep Science about ideas!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a4VvcmqnkhY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study (Paper Explained)", "Time Created": null, "Time Published": "2020-08-20T09:46:35Z", "Duration": null, "Description": "ai #research #machinelearning Online Reinforcement Learning is a flourishing field with countless methods for practitioners to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dPsXxLyqpfs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "World Models", "Time Created": null, "Time Published": "2018-04-07T13:36:31Z", "Duration": null, "Description": "Authors: David Ha, J\u00fcrgen Schmidhuber Abstract: We explore building generative neural network models of popular ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "q6Kyvy1zLwQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "BERTology Meets Biology: Interpreting Attention in Protein Language Models (Paper Explained)", "Time Created": null, "Time Published": "2020-07-02T13:27:53Z", "Duration": null, "Description": "Proteins are the workhorses of almost all cellular functions and a core component of life. But despite their versatility, all proteins ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iAR8LkkMMIM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity", "Time Created": null, "Time Published": "2021-01-22T19:38:10Z", "Duration": null, "Description": "ai #technology #switchtransformer Scale is the next frontier for AI. Google Brain uses sparsity and hard routing to massively ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "W3mrgqtm5R4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] BLOOM: 176B Open-Source | Chinese Brain-Scale Computer | Meta AI: No Language Left Behind", "Time Created": null, "Time Published": "2022-07-27T20:22:22Z", "Duration": null, "Description": "mlnews #bloom #ai Today we look at all the recent giant language models in the AI world! OUTLINE: 0:00 - Intro 0:55 - BLOOM: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "5skIqoO3ku0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "OpenAI Embeddings (and Controversy?!)", "Time Created": null, "Time Published": "2022-02-07T20:10:42Z", "Duration": null, "Description": "mlnews #openai #embeddings COMMENTS DIRECTLY FROM THE AUTHOR (thanks a lot for reaching out Arvind :) ): 1.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "af6WPqvzjjk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Text-to-Image models are taking over! (Imagen, DALL-E 2, Midjourney, CogView 2 & more)", "Time Created": null, "Time Published": "2022-08-07T12:54:12Z", "Duration": null, "Description": "mlnews #dalle #imagen All things text-to-image models like DALL-E and Imagen! OUTLINE: 0:00 - Intro 0:30 - Imagen: Google's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dND-7llwrpw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Grokking: Generalization beyond Overfitting on small algorithmic datasets (Paper Explained)", "Time Created": null, "Time Published": "2021-10-06T20:12:52Z", "Duration": null, "Description": "grokking #openai #deeplearning Grokking is a phenomenon when a neural network suddenly learns a pattern in the dataset and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FC-R4MlIqrc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Cedille French Language Model | YOU Search Engine | AI Finds Profitable MEME TOKENS", "Time Created": null, "Time Published": "2021-11-18T14:54:52Z", "Duration": null, "Description": "mlnews #cedille #wmt Only the greatest of news from the world of Machine Learning. OUTLINE: 0:00 - Sponsor: Weights & Biases ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "56GW1IlWgMg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning model-based planning from scratch", "Time Created": null, "Time Published": "2017-08-09T06:02:41Z", "Duration": null, "Description": "https://arxiv.org/abs/1707.06170 Abstract: Conventional wisdom holds that model-based planning is a powerful approach to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "T35ba_VXkMY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DETR: End-to-End Object Detection with Transformers (Paper Explained)", "Time Created": null, "Time Published": "2020-05-28T15:09:01Z", "Duration": null, "Description": "Object detection in images is a notoriously hard task! Objects can be of a wide variety of classes, can be numerous or absent, they ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AJwnbSP_rq8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "GPT-NeoX-20B - Open-Source huge language model by EleutherAI (Interview w/ co-founder Connor Leahy)", "Time Created": null, "Time Published": "2022-02-04T16:49:40Z", "Duration": null, "Description": "eleuther #gptneo #gptj EleutherAI announces GPT-NeoX-20B, a 20 billion parameter open-source language model, inspired by ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fvctpYph8Pc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Do ImageNet Classifiers Generalize to ImageNet? (Paper Explained)", "Time Created": null, "Time Published": "2020-04-27T12:42:47Z", "Duration": null, "Description": "Has the world overfitted to ImageNet? What if we collect another dataset in exactly the same fashion? This paper gives a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZVVnvZdUMUk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks", "Time Created": null, "Time Published": "2020-04-13T14:51:36Z", "Duration": null, "Description": "Stunning evidence for the hypothesis that neural networks work so well because their random initialization almost certainly ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rFwQDDbYTm4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Classic] Playing Atari with Deep Reinforcement Learning (Paper Explained)", "Time Created": null, "Time Published": "2020-07-26T13:00:23Z", "Duration": null, "Description": "ai #dqn #deepmind After the initial success of deep neural networks, especially convolutional neural networks on supervised ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xnChXNUNS2A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] This AI completes Wikipedia! Meta AI Sphere | Google Minerva | GPT-3 writes a paper", "Time Created": null, "Time Published": "2022-07-31T13:33:13Z", "Duration": null, "Description": "mlnews #ai #minerva This episode is all about models that reason. OUTLINE: 0:00 - Intro 0:35 - Meta AI learns Wikipedia citations ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZfDZRX3WiJg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "VirTex: Learning Visual Representations from Textual Annotations (Paper Explained)", "Time Created": null, "Time Published": "2020-06-12T17:28:15Z", "Duration": null, "Description": "Pre-training a CNN backbone for visual transfer learning has recently seen a big push into the direction of incorporating more data ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CA8JPbJ75tY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "CornerNet: Detecting Objects as Paired Keypoints (Paper Explained)", "Time Created": null, "Time Published": "2020-06-05T13:31:46Z", "Duration": null, "Description": "Many object detectors focus on locating the center of the object they want to find. However, this leaves them with the secondary ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wTzvKB6D_34", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "How far can we scale up? Deep Learning's Diminishing Returns (Article Review)", "Time Created": null, "Time Published": "2021-10-02T14:24:54Z", "Duration": null, "Description": "deeplearning #co2 #cost Deep Learning has achieved impressive results in the last years, not least due to the massive increases ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pZyxlf6l0N8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Thinking While Moving: Deep Reinforcement Learning with Concurrent Control", "Time Created": null, "Time Published": "2020-04-23T13:26:07Z", "Duration": null, "Description": "Classic RL \"stops\" the world whenever the Agent computes a new action. This paper considers a more realistic scenario where ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hMO6rbMAPew", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Adversarial Examples Are Not Bugs, They Are Features", "Time Created": null, "Time Published": "2019-05-14T13:45:57Z", "Duration": null, "Description": "Abstract: Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WknN4E-y44E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Research Conference ICML drops their acceptance rate | Area Chairs instructed to be more picky", "Time Created": null, "Time Published": "2021-05-11T17:47:17Z", "Duration": null, "Description": "icml #machinelearning #conference In a controversial move, ICML Area Chairs were instructed to raise the bar on acceptance to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rNkHjZtH0RQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NFNets: High-Performance Large-Scale Image Recognition Without Normalization (ML Paper Explained)", "Time Created": null, "Time Published": "2021-02-14T16:51:10Z", "Duration": null, "Description": "nfnets #deepmind #machinelearning Batch Normalization is a core component of modern deep learning. It enables training at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "o75ybZ-6Uu8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Dreamer v2: Mastering Atari with Discrete World Models (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-02-19T16:11:18Z", "Duration": null, "Description": "dreamer #deeprl #reinforcementlearning Model-Based Reinforcement Learning has been lagging behind Model-Free RL on Atari ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MgJ3JsE3Tqo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - VOS: Learning What You Don't Know by Virtual Outlier Synthesis", "Time Created": null, "Time Published": "2022-03-14T14:01:38Z", "Duration": null, "Description": "deeplearning #objectdetection #outliers An interview with the authors of \"Virtual Outlier Synthesis\". Watch the paper review video ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "KXEEqcwXn8w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "A neurally plausible model learns successor representations in partially observable environments", "Time Created": null, "Time Published": "2019-11-07T10:15:19Z", "Duration": null, "Description": "Successor representations are a mid-point between model-based and model-free reinforcement learning. This paper learns ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tC01FRB0M7w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Turing-NLG, DeepSpeed and the ZeRO optimizer", "Time Created": null, "Time Published": "2020-02-11T14:56:20Z", "Duration": null, "Description": "Microsoft has trained a 17-billion parameter language model that achieves state-of-the-art perplexity. This video takes a look at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "i4H0kjxrias", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reformer: The Efficient Transformer", "Time Created": null, "Time Published": "2020-01-22T10:01:26Z", "Duration": null, "Description": "The Transformer for the masses! Reformer solves the biggest problem with the famous Transformer model: Its huge resource ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jltgNGt8Lpg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Neural Ordinary Differential Equations", "Time Created": null, "Time Published": "2019-02-19T05:12:20Z", "Duration": null, "Description": "https://arxiv.org/abs/1806.07366 Abstract: We introduce a new family of deep neural network models. Instead of specifying a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1aO-uHXbzmQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Jukebox: A Generative Model for Music (Paper Explained)", "Time Created": null, "Time Published": "2020-05-02T11:06:26Z", "Duration": null, "Description": "This generative model for music can make entire songs with remarkable quality and consistency. It can be conditioned on genre, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a0f07M2uj_A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Backpropagation and the brain", "Time Created": null, "Time Published": "2020-04-20T13:40:41Z", "Duration": null, "Description": "Geoffrey Hinton and his co-authors describe a biologically plausible variant of backpropagation and report evidence that such an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RZ7JiAk9azY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "My GitHub (Trash code I wrote during PhD)", "Time Created": null, "Time Published": "2021-06-08T17:46:22Z", "Duration": null, "Description": "phdlife #github #researchcode A brief browse through my public GitHub and musings about my old code.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l_3zj6HeWUE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Group Normalization (Paper Explained)", "Time Created": null, "Time Published": "2020-05-12T14:05:56Z", "Duration": null, "Description": "The dirty little secret of Batch Normalization is its intrinsic dependence on the training batch size. Group Normalization attempts to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oz5yZc9ULAc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos (Paper Explained)", "Time Created": null, "Time Published": "2022-06-26T21:58:34Z", "Duration": null, "Description": "openai #vpt #minecraft Minecraft is one of the harder challenges any RL agent could face. Episodes are long, and the world is ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a6v92P0EbJc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Neural Architecture Search without Training (Paper Explained)", "Time Created": null, "Time Published": "2020-07-21T13:00:01Z", "Duration": null, "Description": "ai #research #machinelearning Neural Architecture Search is typically very slow and resource-intensive. A meta-controller has to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aX8phGhG8VQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Does GPT-3 lie? - Misinformation and fear-mongering around the TruthfulQA dataset", "Time Created": null, "Time Published": "2021-09-21T13:43:28Z", "Duration": null, "Description": "gpt-3 #truth #conspiracy A new benchmark paper has created quite an uproar in the community. TruthfulQA is a dataset of 817 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Nfry2b4RFI4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Investigating Human Priors for Playing Video Games (Paper & Demo)", "Time Created": null, "Time Published": "2020-05-20T13:52:49Z", "Duration": null, "Description": "Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vVRC-0VKPrg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning Rate Grafting: Transferability of Optimizer Tuning (Machine Learning Research Paper Review)", "Time Created": null, "Time Published": "2021-11-20T15:47:46Z", "Duration": null, "Description": "grafting #adam #sgd The last years in deep learning research have given rise to a plethora of different optimization algorithms, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "H5vpBCLo74U", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "XLNet: Generalized Autoregressive Pretraining for Language Understanding", "Time Created": null, "Time Published": "2019-07-03T10:51:44Z", "Duration": null, "Description": "Abstract: With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9Kec_7WFyp0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Growing Neural Cellular Automata", "Time Created": null, "Time Published": "2020-02-12T08:36:06Z", "Duration": null, "Description": "The Game of Life on steroids! This model learns to grow complex patterns in an entirely local way. Each cell is trained to listen to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "h3ij3F3cPIk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DINO: Emerging Properties in Self-Supervised Vision Transformers (Facebook AI Research Explained)", "Time Created": null, "Time Published": "2021-05-01T19:53:03Z", "Duration": null, "Description": "dino #facebook #selfsupervised Self-Supervised Learning is the final frontier in Representation Learning: Getting useful features ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CRlN-cYFxTk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis (ML Research Paper Explained)", "Time Created": null, "Time Published": "2021-04-19T15:21:29Z", "Duration": null, "Description": "nerf #neuralrendering #deeplearning View Synthesis is a tricky problem, especially when only given a sparse set of images as an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lqtlua-Ylts", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication", "Time Created": null, "Time Published": "2020-04-01T13:10:40Z", "Duration": null, "Description": "Peer Review is outdated and ineffective. SOAR is a new and revolutionary way to distribute scientific reviewing and scale to the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8Oy7o3Yu-Xo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Efficient and Modular Implicit Differentiation (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-06-11T21:14:12Z", "Duration": null, "Description": "implicitfunction #jax #autodiff Many problems in Machine Learning involve loops of inner and outer optimization. Finding update ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "smUHQndcmOY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind's Flamingo Image-Text model | Locked-Image Tuning | Jurassic X & MRKL", "Time Created": null, "Time Published": "2022-05-13T15:47:15Z", "Duration": null, "Description": "flamingo #mlnews #tech Your updates directly from the state of the art in Machine Learning! OUTLINE: 0:00 - Intro 0:30 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "agXIYMCICcc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Imagination-Augmented Agents for Deep Reinforcement Learning", "Time Created": null, "Time Published": "2017-08-04T07:15:56Z", "Duration": null, "Description": "Commentary of https://arxiv.org/abs/1707.06203 Abstract We introduce Imagination-Augmented Agents (I2As), a novel ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dPsXxLyqpfs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "World Models", "Time Created": null, "Time Published": "2018-04-07T13:36:31Z", "Duration": null, "Description": "Authors: David Ha, J\u00fcrgen Schmidhuber Abstract: We explore building generative neural network models of popular ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "n1SXlK5rhR8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Drama] Yann LeCun against Twitter on Dataset Bias", "Time Created": null, "Time Published": "2020-06-22T13:20:42Z", "Duration": null, "Description": "Yann LeCun points out an instance of dataset bias and proposes a sensible solution. People are not happy about it. Original ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "G2sr1g6rLdE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Radioactive data: tracing through training (Paper Explained)", "Time Created": null, "Time Published": "2020-08-26T12:31:39Z", "Duration": null, "Description": "ai #research #privacy Data is the modern gold. Neural classifiers can improve their performance by training on more data, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Cs_j-oNwGgg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Concept Learning with Energy-Based Models (Paper Explained)", "Time Created": null, "Time Published": "2020-05-11T13:59:56Z", "Duration": null, "Description": "This is a hard paper! Energy-functions are typically a mere afterthought in current machine learning. A core function of the Energy ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "utuz7wBGjKM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[News] OpenAI Model Generates Python Code", "Time Created": null, "Time Published": "2020-05-21T16:34:09Z", "Duration": null, "Description": "This code completion engine can write an entire function from just the name! OpenAI demonstrates what happens when you learn ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SY5PvZrJhLE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "GPT-3: Language Models are Few-Shot Learners (Paper Explained)", "Time Created": null, "Time Published": "2020-05-29T15:13:36Z", "Duration": null, "Description": "gpt3 #openai #gpt-3 How far can you go with ONLY language modeling? Can a large enough language model perform NLP task ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "S-7r0-oysaU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] OpenAI's Whisper | Meta Reads Brain Waves | AI Wins Art Fair, Annoys Humans", "Time Created": null, "Time Published": "2022-10-02T20:50:43Z", "Duration": null, "Description": "mlnews #openai #ai Everything important going on in the ML world right here! Sponsor: Paperspace ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rvr143crpuU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Accelerating Deep Learning by Focusing on the Biggest Losers", "Time Created": null, "Time Published": "2019-10-07T12:35:36Z", "Duration": null, "Description": "What if you could reduce the time your network trains by only training on the hard examples? This paper proposes to select ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2v0xU2N1cdI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "IT ARRIVED! YouTube sent me a package. (also: Limited Time Merch Deal)", "Time Created": null, "Time Published": "2022-01-27T15:01:04Z", "Duration": null, "Description": "LIMITED TIME MERCH DEAL: http://store.ykilcher.com Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sEG8hD64c_Q", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "TUNIT: Rethinking the Truly Unsupervised Image-to-Image Translation (Paper Explained)", "Time Created": null, "Time Published": "2020-06-16T14:16:24Z", "Duration": null, "Description": "Image-to-Image translation usually requires corresponding samples or at least domain labels of the dataset. This paper removes ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8Oy7o3Yu-Xo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Efficient and Modular Implicit Differentiation (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-06-11T21:14:12Z", "Duration": null, "Description": "implicitfunction #jax #autodiff Many problems in Machine Learning involve loops of inner and outer optimization. Finding update ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WVPE62Gk3EM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Big Bird: Transformers for Longer Sequences (Paper Explained)", "Time Created": null, "Time Published": "2020-08-02T07:49:12Z", "Duration": null, "Description": "ai #nlp #attention The quadratic resource requirements of the attention mechanism are the main roadblock in scaling up ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ru23eWAQ6_E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Do As I Can, Not As I Say: Grounding Language in Robotic Affordances (SayCan - Paper Explained)", "Time Created": null, "Time Published": "2022-04-30T16:26:42Z", "Duration": null, "Description": "saycan #robots #ai Large Language Models are excellent at generating plausible plans in response to real-world problems, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "VQoyypYTz2U", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "All about AI Accelerators: GPU, TPU, Dataflow, Near-Memory, Optical, Neuromorphic & more (w/ Author)", "Time Created": null, "Time Published": "2022-02-20T16:48:36Z", "Duration": null, "Description": "ai #gpu #tpu This video is an interview with Adi Fuchs, author of a series called \"AI Accelerators\", and an expert in modern AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZfDZRX3WiJg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "VirTex: Learning Visual Representations from Textual Annotations (Paper Explained)", "Time Created": null, "Time Published": "2020-06-12T17:28:15Z", "Duration": null, "Description": "Pre-training a CNN backbone for visual transfer learning has recently seen a big push into the direction of incorporating more data ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DdkenV-ZdJU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Weird and Wonderful World of AI Art (w/ Author Jack Morris)", "Time Created": null, "Time Published": "2022-04-04T13:13:08Z", "Duration": null, "Description": "aiart #deeplearning #clip Since the release of CLIP, the world of AI art has seen an unprecedented level of acceleration in what's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qgUegkefocg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Fastformer: Additive Attention Can Be All You Need (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-08-26T13:32:01Z", "Duration": null, "Description": "attention #transformer #fastformer Transformers have become the dominant model class in the last few years for large data, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "waK7AD-AEyc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeurIPS 19 Poster Session", "Time Created": null, "Time Published": "2019-12-11T19:56:52Z", "Duration": null, "Description": "I'm at the poster session and the amount of people here is just crazy.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yPjuAo53uNI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] The Male Only History of Deep Learning", "Time Created": null, "Time Published": "2020-04-22T11:58:28Z", "Duration": null, "Description": "This casting of our field in terms of ideological narrow-sighted group-think is disgusting. Keep Science about ideas!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tC01FRB0M7w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Turing-NLG, DeepSpeed and the ZeRO optimizer", "Time Created": null, "Time Published": "2020-02-11T14:56:20Z", "Duration": null, "Description": "Microsoft has trained a 17-billion parameter language model that achieves state-of-the-art perplexity. This video takes a look at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "agXIYMCICcc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Imagination-Augmented Agents for Deep Reinforcement Learning", "Time Created": null, "Time Published": "2017-08-04T07:15:56Z", "Duration": null, "Description": "Commentary of https://arxiv.org/abs/1707.06203 Abstract We introduce Imagination-Augmented Agents (I2As), a novel ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1aO-uHXbzmQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Jukebox: A Generative Model for Music (Paper Explained)", "Time Created": null, "Time Published": "2020-05-02T11:06:26Z", "Duration": null, "Description": "This generative model for music can make entire songs with remarkable quality and consistency. It can be conditioned on genre, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "B9PL__gVxLI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DeepMind's AlphaFold 2 Explained! AI Breakthrough in Protein Folding! What we know (& what we don't)", "Time Created": null, "Time Published": "2020-12-01T15:31:42Z", "Duration": null, "Description": "deepmind #biology #ai This is Biology's AlexNet moment! DeepMind solves a 50-year old problem in Protein Folding Prediction.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sbKaUc0tPaY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Odds are Odd: A Statistical Test for Detecting Adversarial Examples", "Time Created": null, "Time Published": "2019-02-20T05:12:21Z", "Duration": null, "Description": "https://arxiv.org/abs/1902.04818 Abstract: We investigate conditions under which test statistics exist that can reliably detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ahRPdiCop3E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Deep Networks Are Kernel Machines (Paper Explained)", "Time Created": null, "Time Published": "2021-02-04T14:36:15Z", "Duration": null, "Description": "deeplearning #kernels #neuralnetworks Full Title: Every Model Learned by Gradient Descent Is Approximately a Kernel Machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Nq3auVtvd9Q", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Classic] ImageNet Classification with Deep Convolutional Neural Networks (Paper Explained)", "Time Created": null, "Time Published": "2020-07-23T13:00:13Z", "Duration": null, "Description": "ai #research #alexnet AlexNet was the start of the deep learning revolution. Up until 2012, the best computer vision systems relied ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BTLCdge7uSQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning", "Time Created": null, "Time Published": "2019-11-02T11:23:04Z", "Duration": null, "Description": "DeepMind's new agent to tackle yet another Esport: Starcraft II. This agent uses deep reinforcement learning with a new technique ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "k1GOF2jmX7c", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Big Transfer (BiT): General Visual Representation Learning (Paper Explained)", "Time Created": null, "Time Published": "2020-05-09T13:28:25Z", "Duration": null, "Description": "One CNN to rule them all! BiT is a pre-trained ResNet that can be used as a starting point for any visual task. This paper explains ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DYBmD88vpiA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Object-Centric Learning with Slot Attention (Paper Explained)", "Time Created": null, "Time Published": "2020-06-30T17:10:35Z", "Duration": null, "Description": "Visual scenes are often comprised of sets of independent objects. Yet, current vision models make no assumptions about the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "p-zOeQCoG9c", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Weight Standardization (Paper Explained)", "Time Created": null, "Time Published": "2020-05-15T14:11:14Z", "Duration": null, "Description": "It's common for neural networks to include data normalization such as BatchNorm or GroupNorm. This paper extends the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "g08NkNWmZTA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "XCiT: Cross-Covariance Image Transformers (Facebook AI Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-06-23T12:25:53Z", "Duration": null, "Description": "xcit #transformer #attentionmechanism After dominating Natural Language Processing, Transformers have taken over Computer ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hMO6rbMAPew", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Adversarial Examples Are Not Bugs, They Are Features", "Time Created": null, "Time Published": "2019-05-14T13:45:57Z", "Duration": null, "Description": "Abstract: Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DiNzQP7kK-s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Descending through a Crowded Valley -- Benchmarking Deep Learning Optimizers (Paper Explained)", "Time Created": null, "Time Published": "2020-10-11T12:46:39Z", "Duration": null, "Description": "ai #research #optimization Deep Learning famously gives rise to very complex, non-linear optimization problems that cannot be ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "u1_qMdb0kYU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "GPT-2: Language Models are Unsupervised Multitask Learners", "Time Created": null, "Time Published": "2019-02-18T16:11:42Z", "Duration": null, "Description": "A look at OpenAI's new GPT-2 model and the surrounding controversy. https://blog.openai.com/better-language-models/ Abstract: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gJR28onlqzs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "How much memory does Longformer use?", "Time Created": null, "Time Published": "2020-04-25T12:51:24Z", "Duration": null, "Description": "A calculation of the memory requirements of the Longformer. Original video: https://youtu.be/_8KNb5iqblE Paper: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NAJOZTNkhlI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Language Models are Open Knowledge Graphs (Paper Explained)", "Time Created": null, "Time Published": "2020-11-02T14:02:08Z", "Duration": null, "Description": "ai #research #nlp Knowledge Graphs are structured databases that capture real-world entities and their relations to each other.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2h4tRsQzipQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Autoregressive Diffusion Models (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-11-10T13:24:24Z", "Duration": null, "Description": "machinelearning #ardm #generativemodels Diffusion models have made large advances in recent months as a new type of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nXGHJTtFYRU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Dynamic Routing Between Capsules", "Time Created": null, "Time Published": "2019-09-04T14:02:31Z", "Duration": null, "Description": "Geoff Hinton's next big idea! Capsule Networks are an alternative way of implementing neural networks by dividing each layer into ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NeGJAUSQEJI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Improving Intrinsic Exploration with Language Abstractions (Machine Learning Paper Explained)", "Time Created": null, "Time Published": "2022-04-01T18:51:58Z", "Duration": null, "Description": "reinforcementlearning #ai #explained Exploration is one of the oldest challenges for Reinforcement Learning algorithms, with no ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "U0mxx7AoNz0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Player of Games: All the games, one algorithm! (w/ author Martin Schmid)", "Time Created": null, "Time Published": "2022-01-02T12:34:43Z", "Duration": null, "Description": "playerofgames #deepmind #alphazero Special Guest: First author Martin Schmid (https://twitter.com/Lifrordi) Games have been ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MgJ3JsE3Tqo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - VOS: Learning What You Don't Know by Virtual Outlier Synthesis", "Time Created": null, "Time Published": "2022-03-14T14:01:38Z", "Duration": null, "Description": "deeplearning #objectdetection #outliers An interview with the authors of \"Virtual Outlier Synthesis\". Watch the paper review video ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IaS72aHrJKE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Fourier Neural Operator for Parametric Partial Differential Equations (Paper Explained)", "Time Created": null, "Time Published": "2020-11-22T13:50:36Z", "Duration": null, "Description": "ai #research #engineering Numerical solvers for Partial Differential Equations are notoriously slow. They need to evolve their ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "uwfVxckuq50", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Why AI is Harder Than We Think (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-04-30T16:02:42Z", "Duration": null, "Description": "aiwinter #agi #embodiedcognition The AI community has gone through regular cycles of AI Springs, where rapid progress gave ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qS-iYnp00uc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Parti - Scaling Autoregressive Models for Content-Rich Text-to-Image Generation (Paper Explained)", "Time Created": null, "Time Published": "2022-06-23T22:38:33Z", "Duration": null, "Description": "parti #ai #aiart Parti is a new autoregressive text-to-image model that shows just how much scale can achieve. This model's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "O_dJ31T01i8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments (Review)", "Time Created": null, "Time Published": "2022-03-18T12:14:08Z", "Duration": null, "Description": "multitasklearning #biology #neuralnetworks Catastrophic forgetting is a big problem in mutli-task and continual learning.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rR5_emVeyBk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "AI made this music video | What happens when OpenAI's CLIP meets BigGAN?", "Time Created": null, "Time Published": "2021-05-18T14:47:54Z", "Duration": null, "Description": "artificialintelligence #musicvideo #clip I used OpenAI's CLIP model and BigGAN to create a music video that goes along with the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hQEnzdLkPj4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning To Classify Images Without Labels (Paper Explained)", "Time Created": null, "Time Published": "2020-06-03T13:22:28Z", "Duration": null, "Description": "How do you learn labels without labels? How do you classify images when you don't know what to classify them into? This paper ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2ethDz9KnLk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The hidden dangers of loading open-source AI models (ARBITRARY CODE EXPLOIT!)", "Time Created": null, "Time Published": "2022-09-02T20:16:53Z", "Duration": null, "Description": "huggingface #pickle #exploit Did you know that something as simple as loading a model can execute arbitrary code on your ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-YiMVR3HEuY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reinforcement Learning with Unsupervised Auxiliary Tasks", "Time Created": null, "Time Published": "2017-08-28T06:53:30Z", "Duration": null, "Description": "https://arxiv.org/abs/1611.05397 Abstract: Deep reinforcement learning agents have achieved state-of-the-art results by directly ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hg2Q_O5b9w4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "CURL: Contrastive Unsupervised Representations for Reinforcement Learning", "Time Created": null, "Time Published": "2020-04-11T11:04:57Z", "Duration": null, "Description": "Contrastive Learning has been an established method in NLP and Image classification. The authors show that with relatively ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "LfUsGv-ESbc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Code] How to use Facebook's DETR object detection algorithm in Python (Full Tutorial)", "Time Created": null, "Time Published": "2020-05-30T13:17:04Z", "Duration": null, "Description": "Watch my as I struggle my way up the glorious path of using the DETR object detection model in PyTorch. Original Video on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xJrKIPwVwGM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Rethinking Attention with Performers (Paper Explained)", "Time Created": null, "Time Published": "2020-10-26T16:57:35Z", "Duration": null, "Description": "ai #research #attention Transformers have huge memory and compute requirements because they construct an Attention matrix, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "j4xgkjWlfL4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "OpenAI DALL\u00b7E: Creating Images from Text (Blog Post Explained)", "Time Created": null, "Time Published": "2021-01-06T13:49:24Z", "Duration": null, "Description": "openai #science #gpt3 OpenAI's newest model, DALL\u00b7E, shows absolutely amazing abilities in generating high-quality images ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Nfry2b4RFI4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Investigating Human Priors for Playing Video Games (Paper & Demo)", "Time Created": null, "Time Published": "2020-05-20T13:52:49Z", "Duration": null, "Description": "Why are humans so good at video games? Maybe it's because a lot of games are designed with humans in mind. What happens if ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pBau7umFhjQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Topographic VAEs learn Equivariant Capsules (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-09-20T20:01:59Z", "Duration": null, "Description": "tvae #topographic #equivariant Variational Autoencoders model the latent space as a set of independent Gaussian random ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NJCLUzkn-sA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "EfficientZero: Mastering Atari Games with Limited Data (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-11-03T15:54:39Z", "Duration": null, "Description": "efficientzero #muzero #atari Reinforcement Learning methods are notoriously data-hungry. Notably, MuZero learns a latent world ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hv3UO3G0Ofo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation (Paper Explained)", "Time Created": null, "Time Published": "2020-08-28T13:06:20Z", "Duration": null, "Description": "ai #machinelearning #attention Convolutional Neural Networks have dominated image processing for the last decade, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hIoCn_9QTVU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I COOKED A RECIPE MADE BY A.I. | Cooking with GPT-3 (Don't try this at home)", "Time Created": null, "Time Published": "2021-04-27T14:34:28Z", "Duration": null, "Description": "gpt3 #airecipe #cooking We went to the store and bought a set of completely random ingredients and had OpenAI's GPT-3 come ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yVKiMh2vEWQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] ConvNeXt: Convolutions return | China regulates algorithms | Saliency cropping examined", "Time Created": null, "Time Published": "2022-01-25T14:42:01Z", "Duration": null, "Description": "mlnews #convnext #mt3 Your update on what's new in the Machine Learning world! OUTLINE: 0:00 - Intro 0:15 - ConvNeXt: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BhUWvQmLzSk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ReBeL - Combining Deep Reinforcement Learning and Search for Imperfect-Information Games (Explained)", "Time Created": null, "Time Published": "2020-12-16T13:55:47Z", "Duration": null, "Description": "ai #technology #poker This paper does for Poker what AlphaZero has done for Chess & Go. The combination of Self-Play ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ihg4XDWOy68", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] De-Biasing GPT-3 | RL cracks chip design | NetHack challenge | Open-Source GPT-J", "Time Created": null, "Time Published": "2021-06-16T14:14:33Z", "Duration": null, "Description": "OUTLINE: 0:00 - Intro 0:30 - Google RL creates next-gen TPUs 2:15 - Facebook launches NetHack challenge 3:50 - OpenAI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "LMb5tvW-UoQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Discovering Symbolic Models from Deep Learning with Inductive Biases (Paper Explained)", "Time Created": null, "Time Published": "2020-06-25T14:09:09Z", "Duration": null, "Description": "Neural networks are very good at predicting systems' numerical outputs, but not very good at deriving the discrete symbolic ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RZ7JiAk9azY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "My GitHub (Trash code I wrote during PhD)", "Time Created": null, "Time Published": "2021-06-08T17:46:22Z", "Duration": null, "Description": "phdlife #github #researchcode A brief browse through my public GitHub and musings about my old code.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-sNJd7bANTI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Roomba Avoids Poop | Textless NLP | TikTok Algorithm Secrets | New Schmidhuber Blog", "Time Created": null, "Time Published": "2021-09-16T15:33:23Z", "Duration": null, "Description": "schmidhuber #tiktok #roomba Your regularly irregular update on what's happening in the world of Machine Learning. OUTLINE: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_c6A33Fg5Ns", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DeBERTa: Decoding-enhanced BERT with Disentangled Attention (Machine Learning Paper Explained)", "Time Created": null, "Time Published": "2021-02-25T17:26:39Z", "Duration": null, "Description": "deberta #bert #huggingface DeBERTa by Microsoft is the next iteration of BERT-style Self-Attention Transformer models, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hHZSA9z_abE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "STOCHASTIC MEME DESCENT - Deep Learning Meme Review - Episode 2 (Part 2 of 2)", "Time Created": null, "Time Published": "2021-01-17T09:55:02Z", "Duration": null, "Description": "memes #science #ai Part 2 of Antonio and me examining the latest and greatest of deep learning memes. Music: Sunshower ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ok44otx90D4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Feature Visualization & The OpenAI microscope", "Time Created": null, "Time Published": "2020-04-17T09:47:23Z", "Duration": null, "Description": "A closer look at the OpenAI microscope, a database of visualizations of the inner workings of ImageNet classifiers, along with an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YBlNQK0Ao6g", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Image GPT: Generative Pretraining from Pixels (Paper Explained)", "Time Created": null, "Time Published": "2020-06-18T13:24:24Z", "Duration": null, "Description": "BERT and GPT-2/3 have shown the enormous power of using generative models as pre-training for classification tasks. However ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Uumd2zOOz60", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "How I Read a Paper: Facebook's DETR (Video Tutorial)", "Time Created": null, "Time Published": "2020-06-24T13:48:00Z", "Duration": null, "Description": "I retrace my first reading of Facebook AI's DETR paper and explain my process of understanding it. OUTLINE: 0:00 - Introduction ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xTzFJIknh7E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "TransCoder: Unsupervised Translation of Programming Languages (Paper Explained)", "Time Created": null, "Time Published": "2020-06-09T14:07:27Z", "Duration": null, "Description": "Code migration between languages is an expensive and laborious task. To translate from one language to the other, one needs to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XjILIYVLFrI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML Olds] Meta Research Supercluster | OpenAI GPT-Instruct | Google LaMDA | Drones fight Pigeons", "Time Created": null, "Time Published": "2022-02-23T14:52:29Z", "Duration": null, "Description": "mlnews #rsc #gpt3 Some things we've missed in recent weeks! OUTLINE: 0:00 - Intro & Overview 0:40 - Meta builds AI Research ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7DGlElSVYGo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "MEMES IS ALL YOU NEED - Deep Learning Meme Review - Episode 2 (Part 1 of 2)", "Time Created": null, "Time Published": "2020-12-24T23:18:43Z", "Duration": null, "Description": "memes #science #ai Antonio and I critique the creme de la creme of Deep Learning memes. Music: Sunshower - LATASH\u00c1 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qSArFEIoSbo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "RepNet: Counting Out Time - Class Agnostic Video Repetition Counting in the Wild (Paper Explained)", "Time Created": null, "Time Published": "2020-06-23T13:54:48Z", "Duration": null, "Description": "Counting repeated actions in a video is one of the easiest tasks for humans, yet remains incredibly hard for machines. RepNet ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vGFaiLeoLWw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] GPT-3 learns to edit | Google Pathways | Make-A-Scene | CLIP meets GamePhysics | DouBlind", "Time Created": null, "Time Published": "2022-03-30T21:27:25Z", "Duration": null, "Description": "mlnews #gpt3 #pathways Your updates on the latest and greatest from the depths of Machine Learning! Sponsor: Weights ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3baFTP0uYOc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Training more effective learned optimizers, and using them to train themselves (Paper Explained)", "Time Created": null, "Time Published": "2020-10-03T16:06:32Z", "Duration": null, "Description": "ai #research #optimization Optimization is still the domain of hand-crafted, simple algorithms. An ML engineer not only has to pick ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "p3sAF3gVMMA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Deep Learning for Symbolic Mathematics", "Time Created": null, "Time Published": "2020-02-24T16:55:45Z", "Duration": null, "Description": "This model solves integrals and ODEs by doing seq2seq! https://arxiv.org/abs/1912.01412 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8l-TDqpoUQs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "SynFlow: Pruning neural networks without any data by iteratively conserving synaptic flow", "Time Created": null, "Time Published": "2020-06-14T13:48:08Z", "Duration": null, "Description": "The Lottery Ticket Hypothesis has shown that it's theoretically possible to prune a neural network at the beginning of training and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-buULmf7dec", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Decision Transformer: Reinforcement Learning via Sequence Modeling (Research Paper Explained)", "Time Created": null, "Time Published": "2021-06-05T16:54:02Z", "Duration": null, "Description": "decisiontransformer #reinforcementlearning #transformer Proper credit assignment over long timespans is a fundamental problem ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a0f07M2uj_A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Backpropagation and the brain", "Time Created": null, "Time Published": "2020-04-20T13:40:41Z", "Duration": null, "Description": "Geoffrey Hinton and his co-authors describe a biologically plausible variant of backpropagation and report evidence that such an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_EDr3ryrT_Y", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Typical Decoding for Natural Language Generation (Get more human-like outputs from language models!)", "Time Created": null, "Time Published": "2022-03-25T20:08:04Z", "Duration": null, "Description": "deeplearning #nlp #sampling Modern language models like T5 or GPT-3 achieve remarkably low perplexities on both training ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vVRC-0VKPrg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning Rate Grafting: Transferability of Optimizer Tuning (Machine Learning Research Paper Review)", "Time Created": null, "Time Published": "2021-11-20T15:47:46Z", "Duration": null, "Description": "grafting #adam #sgd The last years in deep learning research have given rise to a plethora of different optimization algorithms, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eCH0M4wzKJs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "WHO ARE YOU? 10k Subscribers Special (w/ Channel Analytics)", "Time Created": null, "Time Published": "2020-05-07T14:18:26Z", "Duration": null, "Description": "An in-depth look at this channel's analytics. Links: YouTube: https://www.youtube.com/c/yannickilcher Twitter: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cIUtRNhY6Rw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "TAPAS: Weakly Supervised Table Parsing via Pre-training (Paper Explained)", "Time Created": null, "Time Published": "2020-05-05T13:41:35Z", "Duration": null, "Description": "Answering complex questions about tabular information is hard. No two tables are alike and sometimes the answer you're looking ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qlB0TPBQ7YY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Transformer Memory as a Differentiable Search Index (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2022-04-16T15:40:13Z", "Duration": null, "Description": "dsi #search #google Search engines work by building an index and then looking up things in it. Usually, that index is a separate ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "X2k7n4FuI7c", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding&Generation", "Time Created": null, "Time Published": "2022-03-23T19:44:37Z", "Duration": null, "Description": "blip #review #ai Cross-modal pre-training has been all the rage lately in deep learning, especially training vision and language ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lvYVuOmUVs8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "OpenAI tackles Math - Formal Mathematics Statement Curriculum Learning (Paper Explained)", "Time Created": null, "Time Published": "2022-03-05T14:58:01Z", "Duration": null, "Description": "openai #math #imo Formal mathematics is a challenging area for both humans and machines. For humans, formal proofs require ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9-o2aAoN0rY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Fast reinforcement learning with generalized policy updates (Paper Explained)", "Time Created": null, "Time Published": "2020-08-23T13:06:02Z", "Duration": null, "Description": "ai #research #reinforcementlearning Reinforcement Learning is a powerful tool, but it is also incredibly data-hungry. Given a new ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fEKZC9mta8w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Uber: Deep Learning for ETA | MuZero Video Compression  | Block-NeRF | EfficientNet-X", "Time Created": null, "Time Published": "2022-02-18T16:38:08Z", "Duration": null, "Description": "mlnews #muzero #nerf Your regularly irregular updates on everything new in the ML world! Merch: http://store.ykilcher.com ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yFAuXmcGk2Y", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "SingularityNET - A Decentralized, Open Market and Network for AIs (Whitepaper Explained)", "Time Created": null, "Time Published": "2021-01-29T21:13:21Z", "Duration": null, "Description": "ai #research #blockchain Big Tech is currently dominating the pursuit of ever more capable AI. This happens behind closed doors ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WTB2p4bqtXU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "End-to-End Adversarial Text-to-Speech (Paper Explained)", "Time Created": null, "Time Published": "2020-06-10T14:14:52Z", "Duration": null, "Description": "Text-to-speech engines are usually multi-stage pipelines that transform the signal into many intermediate representations and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "LB4B5FYvtdI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Predictive Coding Approximates Backprop along Arbitrary Computation Graphs (Paper Explained)", "Time Created": null, "Time Published": "2020-11-29T14:04:54Z", "Duration": null, "Description": "ai #biology #neuroscience Backpropagation is the workhorse of modern deep learning and a core component of most frameworks ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hAooAOFRsYc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention (Paper Explained)", "Time Created": null, "Time Published": "2020-07-04T12:39:13Z", "Duration": null, "Description": "ai #attention #transformer #deeplearning Transformers are famous for two things: Their superior performance and their insane ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-Kgxv64aG3o", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ALiBi - Train Short, Test Long: Attention with linear biases enables input length extrapolation", "Time Created": null, "Time Published": "2021-09-02T22:35:08Z", "Duration": null, "Description": "alibi #transformers #attention Transformers are essentially set models that need additional inputs to make sense of sequence data ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_7xpGve9QEE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Future of AI is Self-Organizing and Self-Assembling (w/ Prof. Sebastian Risi)", "Time Created": null, "Time Published": "2022-08-26T18:25:39Z", "Duration": null, "Description": "ai #selforganization #emergence Read Sebastian's article here: https://sebastianrisi.com/self_assembling_ai/ OUTLINE: 0:00 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "i-J4T3uLC9M", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "VOS: Learning What You Don't Know by Virtual Outlier Synthesis (Paper Explained)", "Time Created": null, "Time Published": "2022-03-13T12:50:48Z", "Duration": null, "Description": "vos #outliers #deeplearning Sponsor: Assembly AI Check them out here: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cllFzkvrYmE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "GLOM: How to represent part-whole hierarchies in a neural network (Geoff Hinton's Paper Explained)", "Time Created": null, "Time Published": "2021-02-27T15:47:03Z", "Duration": null, "Description": "glom #hinton #capsules Geoffrey Hinton describes GLOM, a Computer Vision model that combines transformers, neural fields, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "KXEEqcwXn8w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "A neurally plausible model learns successor representations in partially observable environments", "Time Created": null, "Time Published": "2019-11-07T10:15:19Z", "Duration": null, "Description": "Successor representations are a mid-point between model-based and model-free reinforcement learning. This paper learns ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "G7-fRGaCZts", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Google introduces Pathways | OpenAI solves Math Problems | Meta goes First Person", "Time Created": null, "Time Published": "2021-11-05T12:51:43Z", "Duration": null, "Description": "pathways #mlnews #ego4d Your irregular dose of Machine Learning News. OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wZWn7Hm8osA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Gauge Equivariant Convolutional Networks and the Icosahedral CNN", "Time Created": null, "Time Published": "2019-08-13T14:03:03Z", "Duration": null, "Description": "Ever wanted to do a convolution on a Klein Bottle? This paper defines CNNs over manifolds such that they are independent of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "v2GRWzIhaqQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Meta-Learning through Hebbian Plasticity in Random Networks (Paper Explained)", "Time Created": null, "Time Published": "2020-08-12T09:20:25Z", "Duration": null, "Description": "ai #neuroscience #rl Reinforcement Learning is a powerful tool, but it lacks biological plausibility because it learns a fixed policy ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cuyM63ugsxI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "On the Measure of Intelligence by Fran\u00e7ois Chollet - Part 3: The Math (Paper Explained)", "Time Created": null, "Time Published": "2020-06-26T13:49:27Z", "Duration": null, "Description": "In this part, we go over the formal definition of the measure of intelligence. In order to do this, we have to frame and quantify the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ml3Y1ljVSQ8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "PCGRL: Procedural Content Generation via Reinforcement Learning (Paper Explained)", "Time Created": null, "Time Published": "2020-08-04T12:00:15Z", "Duration": null, "Description": "ai #research #gaming Deep RL is usually used to solve games, but this paper turns the process on its head and applies RL to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YOLL8dIhLJI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind controls fusion | Yann LeCun's JEPA architecture | US: AI can't copyright its art", "Time Created": null, "Time Published": "2022-03-04T11:50:07Z", "Duration": null, "Description": "mlnews #deepmind #fusion Updates on what's going on in the ML world! Check out w&b's alerts feature: https://wandb.me/yannic ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MQ89be_685o", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Hardware Lottery (Paper Explained)", "Time Created": null, "Time Published": "2020-09-18T20:27:55Z", "Duration": null, "Description": "ai #research #hardware We like to think that ideas in research succeed because of their merit, but this story is likely incomplete.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-cT-2xvaeks", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Facebook AI adapting robots | Baidu autonomous excavators | Happy Birthday EleutherAI", "Time Created": null, "Time Published": "2021-07-15T11:17:21Z", "Duration": null, "Description": "A look into the happenings of the Machine Learning world. OUTLINE: 0:00 - Intro 0:25 - Facebook AI trains rapidly adapting robots ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nv6oFDp6rNQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Hopfield Networks is All You Need (Paper Explained)", "Time Created": null, "Time Published": "2020-08-09T15:51:38Z", "Duration": null, "Description": "ai #transformer #attention Hopfield Networks are one of the classic models of biological memory networks. This paper generalizes ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gYxJEd3EUKs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Memory-assisted prompt editing to improve GPT-3 after deployment (Machine Learning Paper Explained)", "Time Created": null, "Time Published": "2022-03-28T13:48:00Z", "Duration": null, "Description": "nlp #gpt3 #prompt Large language models such as GPT-3 have enabled many breakthroughs and new applications recently, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9MJTeOaSMTk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Self-driving from VISION ONLY - Tesla's self-driving progress by Andrej Karpathy (Talk Analysis)", "Time Created": null, "Time Published": "2021-07-03T13:00:56Z", "Duration": null, "Description": "tesla #selfdriving #karpathy Tesla is pushing the state-of-the-art in full self-driving, and interestingly, they explicitly switch from ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7OdhtAiPfWY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I BUILT A NEURAL NETWORK IN MINECRAFT | Analog Redstone Network w/ Backprop & Optimizer (NO MODS)", "Time Created": null, "Time Published": "2021-04-14T13:33:43Z", "Duration": null, "Description": "minecraft #neuralnetwork #backpropagation I built an analog neural network in vanilla Minecraft without any mods or command ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "EbHUU-gLyRA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Self-classifying MNIST Digits (Paper Explained)", "Time Created": null, "Time Published": "2020-09-02T09:29:27Z", "Duration": null, "Description": "ai #biology #machinelearning Neural Cellular Automata are models for how living creatures can use local message passing to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Lg97gWXsiQ4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Resolution-robust Large Mask Inpainting with Fourier Convolutions (w/ Author Interview)", "Time Created": null, "Time Published": "2021-12-18T12:09:06Z", "Duration": null, "Description": "lama #inpainting #deeplearning At the end of the video is an interview with the paper authors! LaMa is a system that is amazing at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "povBDxUn1VQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ACCEL: Evolving Curricula with Regret-Based Environment Design (Paper Review)", "Time Created": null, "Time Published": "2022-04-25T18:40:16Z", "Duration": null, "Description": "ai #accel #evolution Automatic curriculum generation is one of the most promising avenues for Reinforcement Learning today.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WYrvh50yu6s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations", "Time Created": null, "Time Published": "2018-12-18T09:18:47Z", "Duration": null, "Description": "https://arxiv.org/abs/1811.12359 Abstract: In recent years, the interest in unsupervised learning of disentangled representations ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "udS2OPohs_s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I TRAINED AN AI TO SOLVE 2+2 (w/ Live Coding)", "Time Created": null, "Time Published": "2020-08-06T16:30:14Z", "Duration": null, "Description": "ai #tech #code A whole bunch of humans are arguing whether 2+2=4 or 2+2=5. Pointless! Let the machines handle this! Colab: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gbG1X8Xq-T8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Enhanced POET: Open-Ended RL through Unbounded Invention of Learning Challenges and their Solutions", "Time Created": null, "Time Published": "2020-04-10T10:11:09Z", "Duration": null, "Description": "The enhanced POET makes some substantial and well-crafted improvements over the original POET algorithm and excels at ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BBp0tHcirtQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "git for research basics: fundamentals, commits, branches, merging", "Time Created": null, "Time Published": "2017-12-13T07:40:17Z", "Duration": null, "Description": "Don't watch this if you already know how to solve a merge conflict :)", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "u5BkO8XMS2I", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "iMAML: Meta-Learning with Implicit Gradients (Paper Explained)", "Time Created": null, "Time Published": "2020-05-19T13:37:21Z", "Duration": null, "Description": "Gradient-based Meta-Learning requires full backpropagation through the inner optimization procedure, which is a computational ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "F5aaXrIMWyU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies (Paper Explained)", "Time Created": null, "Time Published": "2020-04-30T16:17:55Z", "Duration": null, "Description": "Hail the AI Tax Collector! This very visual framework has RL Agents maximize their coins in a tiny world through collecting, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "5IRlUVrEVL8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Deep Ensembles: A Loss Landscape Perspective (Paper Explained)", "Time Created": null, "Time Published": "2020-07-11T12:57:17Z", "Duration": null, "Description": "ai #research #optimization Deep Ensembles work surprisingly well for improving the generalization capabilities of deep neural ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "R5DiLFOMZrc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "TransGAN: Two Transformers Can Make One Strong GAN (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-02-17T16:02:54Z", "Duration": null, "Description": "transformer #gan #machinelearning Generative Adversarial Networks (GANs) hold the state-of-the-art when it comes to image ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "q7QP_lfqnQM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Synthesizer: Rethinking Self-Attention in Transformer Models (Paper Explained)", "Time Created": null, "Time Published": "2020-05-31T14:27:04Z", "Duration": null, "Description": "Do we really need dot-product attention? The attention mechanism is a central part of modern Transformers, mainly due to the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-_2AF9Lhweo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Linformer: Self-Attention with Linear Complexity (Paper Explained)", "Time Created": null, "Time Published": "2020-06-11T13:50:50Z", "Duration": null, "Description": "Transformers are notoriously resource-intensive because their self-attention mechanism requires a squared number of memory ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "k_hUdZJNzkU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "The Dimpled Manifold Model of Adversarial Examples in Machine Learning (Research Paper Explained)", "Time Created": null, "Time Published": "2021-06-27T12:06:18Z", "Duration": null, "Description": "adversarialexamples #dimpledmanifold #security Adversarial Examples have long been a fascinating topic for many Machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-h1KB8ps11A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Datasets for Data-Driven Reinforcement Learning", "Time Created": null, "Time Published": "2020-04-16T18:07:00Z", "Duration": null, "Description": "Offline Reinforcement Learning has come more and more into focus recently in domains where classic on-policy RL algorithms ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "h9w3KffPPmQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] Online Conferences", "Time Created": null, "Time Published": "2020-04-28T15:36:11Z", "Duration": null, "Description": "Are virtual conferences good or bad? What's missing? How do we go forward? Pictures from here: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IiBFqnNu7A8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Planning to Explore via Self-Supervised World Models (Paper Explained)", "Time Created": null, "Time Published": "2020-05-17T14:01:30Z", "Duration": null, "Description": "What can an agent do without any reward? Explore the world! While many formulations of intrinsic rewards exist (Curiosity, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JPX_jSZtszY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeurIPS 2020 Changes to Paper Submission Process", "Time Created": null, "Time Published": "2020-02-21T10:32:41Z", "Duration": null, "Description": "My thoughts on the changes to the paper submission process for NeurIPS 2020. The main new changes are: 1. ACs can desk ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DRy_Mr732yA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Drama] Who invented Contrast Sets?", "Time Created": null, "Time Published": "2020-04-08T12:11:31Z", "Duration": null, "Description": "Funny Twitter spat between researchers arguing who was the first to invent an idea that has probably been around since 1990 :D ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GgHXGpQ60x0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] AI learns to search the Internet | Drawings come to life | New ML journal launches", "Time Created": null, "Time Published": "2021-12-24T12:29:20Z", "Duration": null, "Description": "webgpt #aiart #mlnews The latest and greatest from the Machine Learning world. OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RrvC8YW0pT0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reinforcement Learning Upside Down: Don't Predict Rewards -- Just Map Them to Actions", "Time Created": null, "Time Published": "2019-12-11T02:45:34Z", "Duration": null, "Description": "Schmidhuber thinking outside the box! Upside-Down RL turns RL on its head and constructs a behavior function that uses the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XHGh19Hbx48", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Can Wikipedia Help Offline Reinforcement Learning? (Paper Explained)", "Time Created": null, "Time Published": "2022-02-26T14:02:37Z", "Duration": null, "Description": "wikipedia #reinforcementlearning #languagemodels Transformers have come to overtake many domain-targeted custom models ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FbRcbM4T-50", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning (Paper Explained)", "Time Created": null, "Time Published": "2021-11-30T00:19:40Z", "Duration": null, "Description": "ext5 #transferlearning #exmix The T5 model has been a staple for NLP research for the last years. Both its size and its approach ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AIOE1l1W0Tw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "LAION-5B: 5 billion image-text-pairs dataset (with the authors)", "Time Created": null, "Time Published": "2022-04-22T13:00:44Z", "Duration": null, "Description": "laion #clip #dalle LAION-5B is an open, free dataset consisting of over 5 billion image-text-pairs. Today's video is an interview with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0JlB9gufTw8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "\u221e-former: Infinite Memory Transformer (aka Infty-Former / Infinity-Former, Research Paper Explained)", "Time Created": null, "Time Published": "2021-09-06T12:07:08Z", "Duration": null, "Description": "inftyformer #infinityformer #transformer Vanilla Transformers are excellent sequence models, but suffer from very harsch ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AvHLJqtmQkE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - Typical Decoding for Natural Language Generation", "Time Created": null, "Time Published": "2022-03-26T15:59:28Z", "Duration": null, "Description": "deeplearning #nlp #sampling This is an interview with first author Clara Meister. Paper review video here\u00e9 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "G3pOvrKkFuk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Code] PyTorch sentiment classifier from scratch with Huggingface NLP Library (Full Tutorial)", "Time Created": null, "Time Published": "2020-05-18T13:26:18Z", "Duration": null, "Description": "Huggingface released its newest library called NLP, which gives you easy access to almost any NLP dataset and metric in one ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "C5sWbYwzKyg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "AlphaCode - with the authors!", "Time Created": null, "Time Published": "2022-03-02T23:00:01Z", "Duration": null, "Description": "ai #alphacode #deepmind An interview with the creators of AlphaCode! Paper review video here: https://youtu.be/s9UAOmyah1A ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zWFkUGXjbdo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] Can AI read your emotions? (No, but ...)", "Time Created": null, "Time Published": "2021-05-30T14:51:48Z", "Duration": null, "Description": "facerecognition #emotiondetection #mindreading Face recognition has a bad rep in the ML community. While the technology ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PZypP7PiKi0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Gradient Surgery for Multi-Task Learning", "Time Created": null, "Time Published": "2020-04-21T12:19:54Z", "Duration": null, "Description": "Multi-Task Learning can be very challenging when gradients of different tasks are of severely different magnitudes or point into ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l12GXD0t_RE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Deep Differential System Stability - Learning advanced computations from examples (Paper Explained)", "Time Created": null, "Time Published": "2020-06-13T14:52:28Z", "Duration": null, "Description": "Determining the stability properties of differential systems is a challenging task that involves very advanced symbolic and numeric ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nQDZmf2Yb9k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "PonderNet: Learning to Ponder (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-08-23T12:40:24Z", "Duration": null, "Description": "pondernet #deepmind #machinelearning Humans don't spend the same amount of mental effort on all problems equally. Instead ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "K-cXYoqHxBc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "More Is Different for AI - Scaling Up, Emergence, and Paperclip Maximizers (w/ Jacob Steinhardt)", "Time Created": null, "Time Published": "2022-09-13T21:33:39Z", "Duration": null, "Description": "ai #interview #research Jacob Steinhardt believes that future AI systems will be qualitatively different than the ones we know ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kP-dXK9JEhY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Symbolic Knowledge Distillation: from General Language Models to Commonsense Models (Explained)", "Time Created": null, "Time Published": "2021-10-24T20:59:32Z", "Duration": null, "Description": "gpt3 #knowledge #symbolic Symbolic knowledge models are usually trained on human-generated corpora that are cumbersome ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "D-eg7k8YSfs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Shortcut Learning in Deep Neural Networks", "Time Created": null, "Time Published": "2020-04-18T13:29:14Z", "Duration": null, "Description": "This paper establishes a framework for looking at out-of-distribution generalization failures of modern deep learning as the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "U3zmekzQ8WQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Agent57: Outperforming the Atari Human Benchmark", "Time Created": null, "Time Published": "2020-03-31T15:49:49Z", "Duration": null, "Description": "DeepMind's Agent57 is the first RL agent to outperform humans in all 57 Atari benchmark games. It extends previous algorithms ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "H6Qiegq_36c", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Processing Megapixel Images with Deep Attention-Sampling Models", "Time Created": null, "Time Published": "2019-08-12T13:44:37Z", "Duration": null, "Description": "Current CNNs have to downsample large images before processing them, which can lose a lot of detail information. This paper ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Hdo81GtLC_4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures (Paper Explained)", "Time Created": null, "Time Published": "2020-06-27T16:04:14Z", "Duration": null, "Description": "Backpropagation is one of the central components of modern deep learning. However, it's not biologically plausible, which limits ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Z_kWZpgEZ7w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Multimodal Neurons in Artificial Neural Networks (w/ OpenAI Microscope, Research Paper Explained)", "Time Created": null, "Time Published": "2021-03-05T13:18:21Z", "Duration": null, "Description": "openai #clip #microscope OpenAI does a huge investigation into the inner workings of their recent CLIP model via faceted feature ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "U8Rmfb8aZXE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] NVIDIA GTC'21 | DeepMind buys MuJoCo | Google predicts spreadsheet formulas", "Time Created": null, "Time Published": "2021-10-29T16:07:13Z", "Duration": null, "Description": "gtc21 #mlnews #mujoco Register to GTC'21 and Win a RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 - Sponsor: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Qk4lJdp7ZAs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning World Graphs to Accelerate Hierarchical Reinforcement Learning", "Time Created": null, "Time Published": "2019-08-08T08:56:43Z", "Duration": null, "Description": "The goal of hierarchical reinforcement learning is to divide a task into different levels of coarseness with the top-level agent ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "X4S8F3bwuuw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview: SayCan - Do As I Can, Not As I Say: Grounding Language in Robotic Affordances", "Time Created": null, "Time Published": "2022-05-02T13:12:13Z", "Duration": null, "Description": "saycan #robots #ai This is an interview with the authors Brian Ichter, Karol Hausman, and Fei Xia. Original Paper Review Video: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "J7CrtblmMnU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Is Google Translate Sexist? Gender Stereotypes in Statistical Machine Translation", "Time Created": null, "Time Published": "2021-03-23T15:59:17Z", "Duration": null, "Description": "genderbias #algorithmicfairness #debiasing A brief look into gender stereotypes in Google Translate. The origin is a Tweet ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZOkvFf8JbkA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind builds Gopher | Google builds GLaM | Suicide capsule uses AI to check access", "Time Created": null, "Time Published": "2021-12-21T13:41:16Z", "Duration": null, "Description": "mlnews #gopher #glam Your updates on everything going on in the Machine Learning world. Sponsor: Weights & Biases ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tjbEVY5XIk0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning (Paper Explained)", "Time Created": null, "Time Published": "2020-05-08T13:10:29Z", "Duration": null, "Description": "When AI makes a plan it usually does so step by step, forward in time. But often it is beneficial to define intermediate goals to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zdb8MM94A5c", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Feedback Transformers: Addressing Some Limitations of Transformers with Feedback Memory (Explained)", "Time Created": null, "Time Published": "2021-02-02T15:36:12Z", "Duration": null, "Description": "ai #science #transformers Autoregressive Transformers have taken over the world of Language Modeling (GPT-3). However, in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lmAj0SU_bW0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Axial Attention & MetNet: A Neural Weather Model for Precipitation Forecasting", "Time Created": null, "Time Published": "2020-03-30T12:40:26Z", "Duration": null, "Description": "MetNet is a predictive neural network model for weather prediction. It uses axial attention to capture long-range dependencies.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f2OgP49J7Pg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind tackles Math | Microsoft does more with less | Timnit Gebru launches DAIR", "Time Created": null, "Time Published": "2021-12-10T21:21:28Z", "Duration": null, "Description": "mlnews #deepmind #ai The most trusted model in News! Get started with Weights & Biases here: https://wandb.me/yannic (it's free ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RXwZKzczkF8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] AI Threatens Biological Arms Race", "Time Created": null, "Time Published": "2022-03-21T22:32:41Z", "Duration": null, "Description": "mlnews #gtc22 #ithaca GTC Registration Link: https://ykilcher.com/gtc Your regular updates on what's going on in the ML world!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YrO1v7-KcXs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Deep image reconstruction from human brain activity (Paper Explained)", "Time Created": null, "Time Published": "2020-05-25T15:38:17Z", "Duration": null, "Description": "Can you peek into people's brains? Reading human thoughts is a long-standing dream of the AI field. This paper reads fMRI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "v-ZxzTSpmk4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Gradient Origin Networks (Paper Explained w/ Live Coding)", "Time Created": null, "Time Published": "2020-07-10T13:01:46Z", "Duration": null, "Description": "Neural networks for implicit representations, such as SIRENs, have been very successful at modeling natural signals. However, in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_N_nFzMtWkA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reinforcement Learning, Fast and Slow", "Time Created": null, "Time Published": "2019-05-10T12:47:57Z", "Duration": null, "Description": "Abstract: Deep reinforcement learning (RL) methods have driven impressive advances in artificial intelligence in recent years, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "UjJU13GdL94", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Regularizing Trajectory Optimization with Denoising Autoencoders (Paper Explained)", "Time Created": null, "Time Published": "2020-05-24T15:31:04Z", "Duration": null, "Description": "Can you plan with a learned model of the world? Yes, but there's a catch: The better your planning algorithm is, the more the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FC-R4MlIqrc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Cedille French Language Model | YOU Search Engine | AI Finds Profitable MEME TOKENS", "Time Created": null, "Time Published": "2021-11-18T14:54:52Z", "Duration": null, "Description": "mlnews #cedille #wmt Only the greatest of news from the world of Machine Learning. OUTLINE: 0:00 - Sponsor: Weights & Biases ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qNfCVGbvnJc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "CM3: A Causal Masked Multimodal Model of the Internet (Paper Explained w/ Author Interview)", "Time Created": null, "Time Published": "2022-02-17T23:04:45Z", "Duration": null, "Description": "cm3 #languagemodel #transformer This video contains a paper explanation and an incredibly informative interview with first ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "s9UAOmyah1A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Competition-Level Code Generation with AlphaCode (Paper Review)", "Time Created": null, "Time Published": "2022-03-01T13:15:04Z", "Duration": null, "Description": "ai #alphacode #deepmind AlphaCode is an automated system that can solve competitive programing exercises. The authors ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "EeMhj0sPrhE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Gradients are Not All You Need (Machine Learning Research Paper Explained)", "Time Created": null, "Time Published": "2021-11-16T00:36:11Z", "Duration": null, "Description": "deeplearning #backpropagation #simulation More and more systems are made differentiable, which means that accurate ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xrYhDMqaa4U", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I went to an AI Art Festival in Geneva (AiiA Festival Trip Report)", "Time Created": null, "Time Published": "2021-10-27T13:52:57Z", "Duration": null, "Description": "aiia #ai #art A trip report from the AiiA Festival in Geneva organized by the ImpactAI foundation. OUTLINE: 0:00 - Intro 1:50 - Laura ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eI8xTdcZ6VY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection (Paper Explained)", "Time Created": null, "Time Published": "2020-06-28T15:09:19Z", "Duration": null, "Description": "Object detection often does not occur in a vacuum. Static cameras, such as wildlife traps, collect lots of irregularly sampled data ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lqtlua-Ylts", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "State-of-Art-Reviewing: A Radical Proposal to Improve Scientific Publication", "Time Created": null, "Time Published": "2020-04-01T13:10:40Z", "Duration": null, "Description": "Peer Review is outdated and ineffective. SOAR is a new and revolutionary way to distribute scientific reviewing and scale to the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "W2UT8NjUqrk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions (Paper Explained)", "Time Created": null, "Time Published": "2021-11-27T17:34:17Z", "Duration": null, "Description": "imle #backpropagation #discrete Backpropagation is the workhorse of deep learning, but unfortunately, it only works for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "O9kFX33nUcU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "On the Measure of Intelligence by Fran\u00e7ois Chollet - Part 4: The ARC Challenge (Paper Explained)", "Time Created": null, "Time Published": "2020-07-03T14:23:17Z", "Duration": null, "Description": "In this part, we look at the ARC challenge as a proposed test of machine intelligence. The dataset features 1000 tasks that test ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IIebBjbBevs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "When BERT Plays the Lottery, All Tickets Are Winning (Paper Explained)", "Time Created": null, "Time Published": "2020-05-22T17:45:44Z", "Duration": null, "Description": "BERT is a giant model. Turns out you can prune away many of its components and it still works. This paper analyzes BERT ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RSSVWpBak6s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Linear Transformers Are Secretly Fast Weight Memory Systems (Machine Learning Paper Explained)", "Time Created": null, "Time Published": "2021-02-26T16:12:24Z", "Duration": null, "Description": "fastweights #deeplearning #transformers Transformers are dominating Deep Learning, but their quadratic memory and compute ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hgSGHusDx7M", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Sparse is Enough in Scaling Transformers (aka Terraformer) | ML Research Paper Explained", "Time Created": null, "Time Published": "2021-12-02T01:21:29Z", "Duration": null, "Description": "scalingtransformers #terraformer #sparsity Transformers keep pushing the state of the art in language and other domains, mainly ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "D6osiiEoV0w", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning (w/ Author)", "Time Created": null, "Time Published": "2022-02-16T00:21:02Z", "Duration": null, "Description": "hypertransformer #metalearning #deeplearning This video contains a paper explanation and an interview with author Andrey ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "P38FZrbNHV4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control (Paper Explained)", "Time Created": null, "Time Published": "2021-06-19T15:07:08Z", "Duration": null, "Description": "reiforcementlearning #gan #imitationlearning Learning from demonstrations is a fascinating topic, but what if the demonstrations ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "K3cmxn5znyU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Microsoft trains 530B model | ConvMixer model fits into single tweet | DeepMind profitable", "Time Created": null, "Time Published": "2021-10-20T13:40:13Z", "Duration": null, "Description": "mlnews #turingnlg #convmixer Your latest upates on what's happening in the Machine Learning world. OUTLINE: 0:00 - Intro 0:16 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bFn2xcGi1TQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Faster Neural Network Training with Data Echoing (Paper Explained)", "Time Created": null, "Time Published": "2020-05-13T13:56:56Z", "Duration": null, "Description": "CPUs are often bottlenecks in Machine Learning pipelines. Data fetching, loading, preprocessing and augmentation can be slow ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3HUK2UWzlFA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Parameter Prediction for Unseen Deep Architectures (w/ First Author Boris Knyazev)", "Time Created": null, "Time Published": "2021-11-24T18:26:39Z", "Duration": null, "Description": "deeplearning #neuralarchitecturesearch #metalearning Deep Neural Networks are usually trained from a given parameter ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1VdEw_mGjFk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding (Paper Explained)", "Time Created": null, "Time Published": "2020-07-01T14:21:03Z", "Duration": null, "Description": "Google builds a 600 billion parameter transformer to do massively multilingual, massive machine translation. Interestingly, the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ccBMRryxGog", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Sparse Expert Models (Switch Transformers, GLAM, and more... w/ the Authors)", "Time Created": null, "Time Published": "2022-04-21T08:40:35Z", "Duration": null, "Description": "nlp #sparsity #transformers This video is an interview with Barret Zoph and William Fedus of Google Brain about Sparse Expert ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "to7vCdkLi4s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Reinforcement Learning with Augmented Data (Paper Explained)", "Time Created": null, "Time Published": "2020-05-06T13:02:50Z", "Duration": null, "Description": "This ONE SIMPLE TRICK can take a vanilla RL algorithm to achieve state-of-the-art. What is it? Simply augment your training data ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vxdcX0JTEr0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I took a Swiss train and it was awesome! Train Seat Review - SBB InterCity 1 - Geneva to St. Gallen", "Time Created": null, "Time Published": "2021-10-21T13:58:08Z", "Duration": null, "Description": "sbb #seatreview #travel A friendly parody of Travel Vloggers and Airplane Seat Reviews :) No, SBB did not pay me for this (but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PFMtdR56Q4U", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Blind Chess AI Competition | Graph NNs for traffic | AI gift suggestions", "Time Created": null, "Time Published": "2021-09-03T15:52:21Z", "Duration": null, "Description": "mlnews #chess #neurips OUTLINE: 0:00 - Intro 0:30 - Reconnaissance Blind Chess NeurIPS 2021 Competition 3:40 - Colab Pro ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l5he9JNJqHA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "A critical analysis of self-supervision, or what we can learn from a single image (Paper Explained)", "Time Created": null, "Time Published": "2020-05-26T14:18:55Z", "Duration": null, "Description": "Does self-supervision really need a lot of data? How low can you go? This paper shows that a single image is enough to learn the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iZXsWlSdMGY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[News] Google\u2019s medical AI was super accurate in a lab. Real life was a different story.", "Time Created": null, "Time Published": "2020-05-10T13:10:02Z", "Duration": null, "Description": "A closer look at a story of how the deployment of AI brings its own challenges and what can go wrong.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SPOqoI0zOPQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] AI-generated patent approved | Germany gets an analog to OpenAI | ML cheats video games", "Time Created": null, "Time Published": "2021-08-06T17:01:30Z", "Duration": null, "Description": "mlnews #dabus #alephalpha OUTLINE: 0:00 - Intro 0:20 - Sponsor: Weights & Biases 3:45 - AI legally recognized as patent ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gFkBqD2hbnU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML NEWS] Apple scans your phone | Master Faces beat face recognition | WALL-E is real", "Time Created": null, "Time Published": "2021-08-13T17:43:15Z", "Duration": null, "Description": "mlnews #apple #nolamarck Your update on the latest news in the AI and Machine Learning world. OUTLINE: 0:00 - Intro 0:15 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DkojaN7_f4E", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] New ImageNet SOTA | Uber's H3 hexagonal coordinate system | New text-image-pair dataset", "Time Created": null, "Time Published": "2021-09-24T18:28:27Z", "Duration": null, "Description": "truthfulqa #efficientnet #laion400M Your regularly irregular updates on what's happening in the Machine Learning world.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2PYLNHqxd5A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Expire-Span: Not All Memories are Created Equal: Learning to Forget by Expiring (Paper Explained)", "Time Created": null, "Time Published": "2021-05-24T12:24:30Z", "Duration": null, "Description": "expirespan #nlp #facebookai Facebook AI (FAIR) researchers present Expire-Span, a variant of Transformer XL that dynamically ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "z15JLtAuwVI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "How Apple scans your phone (and how to evade it) - NeuralHash CSAM Detection Algorithm Explained", "Time Created": null, "Time Published": "2021-08-16T11:34:59Z", "Duration": null, "Description": "apple #icloud #privacy Apple recently announced scanning all images uploaded to iCloud for CSAM (child abuse material), and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Z6ea_AbnnCc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "NeurIPS 2019", "Time Created": null, "Time Published": "2019-12-08T21:41:37Z", "Duration": null, "Description": "I'm at the 2019 conference on Neural Information Processing Systems in Vancouver, trying to register, but the line was just so long ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "C7mUYocWdG0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - Transformer Memory as a Differentiable Search Index", "Time Created": null, "Time Published": "2022-04-17T22:14:08Z", "Duration": null, "Description": "neuralsearch #interview #google This is an interview with the authors Yi Tay and Don Metzler. Paper Review Video: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "w3knicSHx5s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Dynamic Inference with Neural Interpreters (w/ author interview)", "Time Created": null, "Time Published": "2022-01-21T16:20:45Z", "Duration": null, "Description": "deeplearning #neuralinterpreter #ai This video includes an interview with the paper's authors! What if we treated deep networks ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qeEO2GECQk0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Evaluating NLP Models via Contrast Sets", "Time Created": null, "Time Published": "2020-04-07T11:40:47Z", "Duration": null, "Description": "Current NLP models are often \"cheating\" on supervised learning tasks by exploiting correlations that arise from the particularities ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zcGOPqFZ4Tk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "AI against Censorship: Genetic Algorithms, The Geneva Project, ML in Security, and more!", "Time Created": null, "Time Published": "2022-02-16T14:23:01Z", "Duration": null, "Description": "security #censorship #ai Most of us conceive the internet as a free and open space where we are able to send traffic between any ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rd3R_G6_UfY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Full Self-Driving is HARD! Analyzing Elon Musk re: Tesla Autopilot on Lex Fridman's Podcast", "Time Created": null, "Time Published": "2022-01-05T20:22:28Z", "Duration": null, "Description": "tesla #fsd #elon Watch the original podcast: https://www.youtube.com/watch?v=DxREm3s1scA An analysis of Elon's appearance ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "z_3Qv4In2ac", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Live Machine Learning Research] Plain Self-Ensembles (I actually DISCOVER SOMETHING) - Part 1", "Time Created": null, "Time Published": "2020-07-06T13:23:54Z", "Duration": null, "Description": "I share my progress of implementing a research idea from scratch. I attempt to build an ensemble model out of students of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gGPv_SYVDC8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "DALL-E 2 by OpenAI is out! Live Reaction", "Time Created": null, "Time Published": "2022-04-06T15:19:54Z", "Duration": null, "Description": "Chatting & Coding.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "H3Bhlan0mE0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Online Education - How I Make My Videos", "Time Created": null, "Time Published": "2020-03-23T09:33:17Z", "Duration": null, "Description": "Just a short overview of tools I use to make my videos. OneNote - https://www.onenote.com iSpring Free Cam ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "i_p5wLoCCiw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[News] Soccer AI FAILS and mixes up ball and referee's bald head.", "Time Created": null, "Time Published": "2020-11-15T12:04:42Z", "Duration": null, "Description": "ai #tech #news This soccer camera is operated by an AI to track the ball. However, the AI has an interesting failure mode and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HGgrSz-jxdU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ARC Challenge Live Coding", "Time Created": null, "Time Published": "2022-07-02T14:37:15Z", "Duration": null, "Description": "Chatting & Coding.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Xp3jR-ttMfo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Noether Networks: Meta-Learning Useful Conserved Quantities (w/ the authors)", "Time Created": null, "Time Published": "2022-01-19T14:58:40Z", "Duration": null, "Description": "deeplearning #noether #symmetries This video includes an interview with first author Ferran Alet! Encoding inductive biases has ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_PyusGsbBPY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Stochastic RNNs without Teacher-Forcing", "Time Created": null, "Time Published": "2018-12-21T13:02:52Z", "Duration": null, "Description": "We present a stochastic non-autoregressive RNN that does not require teacher-forcing for training. The content is based on our ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Z3knUzwuIgo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "One Model For All The Tasks - BLIP (Author Interview)", "Time Created": null, "Time Published": "2022-03-24T21:27:22Z", "Duration": null, "Description": "blip #interview #salesforce Paper Review Video: https://youtu.be/X2k7n4FuI7c Sponsor: Assembly AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AU30czb4iQA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Imputer: Sequence Modelling via Imputation and Dynamic Programming", "Time Created": null, "Time Published": "2020-04-14T12:47:57Z", "Duration": null, "Description": "The imputer is a sequence-to-sequence model that strikes a balance between fully autoregressive models with long inference ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NEkriziVYXo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind does Nowcasting | The Guardian's shady reporting | AI finishes Beethoven's 10th", "Time Created": null, "Time Published": "2021-10-07T13:14:55Z", "Duration": null, "Description": "deepmind #nowcasting #machinelearning Your holy update on what's new in the Machine Learning world. OUTLINE: 0:00 - Intro ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lj-LGrnh1oU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "REALM: Retrieval-Augmented Language Model Pre-Training (Paper Explained)", "Time Created": null, "Time Published": "2020-08-14T15:50:20Z", "Duration": null, "Description": "ai #tech #science Open Domain Question Answering is one of the most challenging tasks in NLP. When answering a question, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nxEr4VNgYOE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Movement Pruning: Adaptive Sparsity by Fine-Tuning (Paper Explained)", "Time Created": null, "Time Published": "2020-06-04T20:06:40Z", "Duration": null, "Description": "Deep neural networks are large models and pruning has become an important part of ML product pipelines, making models small ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gu5UM99qaVc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Nvidia renders CEO | Jurassic-1 larger than GPT-3 | Tortured Phrases reveal Plagiarism", "Time Created": null, "Time Published": "2021-08-18T19:02:59Z", "Duration": null, "Description": "mlnews #nvidia #openai An in-depth look over what's going on in the world of Machine Learning and Artificial intelligence.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wAgO2WZzjn4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Rant] coronavirus", "Time Created": null, "Time Published": "2020-03-25T13:38:20Z", "Duration": null, "Description": "A rant about toilet paper and lockdowns. Links: YouTube: https://www.youtube.com/c/yannickilcher Twitter: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8f5xIMStqF4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] OpenAI removes GPT-3 waitlist | GauGAN2 is amazing | NYC regulates AI hiring tools", "Time Created": null, "Time Published": "2021-12-02T17:57:35Z", "Duration": null, "Description": "mlnews #gaugan #gpt-3 Your weekly dose of ML News! More GauGAN images here: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Rk3MBx20z24", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Apple or iPod??? Easy Fix for Adversarial Textual Attacks on OpenAI's CLIP Model! #Shorts", "Time Created": null, "Time Published": "2021-03-06T16:13:09Z", "Duration": null, "Description": "Shorts #shorts #openai In the paper Multimodal Neurons in Artificial Neural Networks OpenAI suggests that CLIP can be attacked ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1HEdXwEYrGM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Predicting the rules behind - Deep Symbolic Regression for Recurrent Sequences (w/ author interview)", "Time Created": null, "Time Published": "2022-01-29T13:28:10Z", "Duration": null, "Description": "deeplearning #symbolic #research This video includes an interview with first author St\u00e9phane d'Ascoli (https://sdascoli.github.io/).", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kl3aBni87jg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "First Author Interview: AI & formal math (Formal Mathematics Statement Curriculum Learning)", "Time Created": null, "Time Published": "2022-03-06T16:27:24Z", "Duration": null, "Description": "openai #math #imo This is an interview with Stanislas Polu, research engineer at OpenAI and first author of the paper \"Formal ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OGytRmpSN10", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Did I crash the NFT market?", "Time Created": null, "Time Published": "2022-06-01T15:40:04Z", "Duration": null, "Description": "", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ch2O2fwWI-k", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News GERMAN] NVIDIA GTC'21 | DeepMind kauft MuJoCo | Google Lernt Spreadsheet Formeln", "Time Created": null, "Time Published": "2021-10-29T16:07:08Z", "Duration": null, "Description": "gtc21 #mlnews #mujoco Registriere f\u00fcr GTC'21 und gewinne eine RTX 3090: https://nvda.ws/2Y2B5ni OUTLINE: 0:00 - Intro 0:15 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "McpjrsHrEY4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] DeepMind AlphaCode | OpenAI math prover | Meta battles harmful content with AI", "Time Created": null, "Time Published": "2022-02-10T14:25:19Z", "Duration": null, "Description": "mlnews #alphacode #openai The latest and greatest from the world of Machine Learning! Merch: http://store.ykilcher.com ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kEhEbVZQwjM", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[YTalks] Siraj Raval - Stories about YouTube, Plagiarism, and the Dangers of Fame (Interview)", "Time Created": null, "Time Published": "2021-10-31T13:32:57Z", "Duration": null, "Description": "ytalks #siraj #plagiarism A conversation with Siraj Raval about his journey on YouTube, and the perils of fame. OUTLINE: 0:00 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a4P8v8lGFPw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "This Team won the Minecraft RL BASALT Challenge! (Paper Explanation & Interview with the authors)", "Time Created": null, "Time Published": "2022-01-11T21:17:53Z", "Duration": null, "Description": "minerl #minecraft #deeplearning The MineRL BASALT challenge has no reward functions or technical descriptions of what's to be ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bw1kiLMQFKU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] EU regulates AI, China trains 1.75T model, Google's oopsie, Everybody cheers for fraud.", "Time Created": null, "Time Published": "2021-06-09T14:06:30Z", "Duration": null, "Description": "mlnews #wudao #academicfraud OUTLINE: 0:00 - Intro 0:25 - EU seeks to regulate AI 2:45 - AI COVID detection systems are all ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6_q9DbX35kk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Hugging Face course | GAN Theft Auto | AI Programming Puzzles | PyTorch 1.9 Released", "Time Created": null, "Time Published": "2021-06-24T12:35:09Z", "Duration": null, "Description": "mlnews #gta #weather In this week's ML News, we look at the latest developments in the Machine Learning and AI world with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qFRfnIRMNlk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization (Paper Explained)", "Time Created": null, "Time Published": "2020-07-05T15:25:42Z", "Duration": null, "Description": "machinelearning #ai #google The high-level architecture of CNNs has not really changed over the years. We tend to build ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vB_hQ5NmtPs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Interview] Mark Ledwich - Algorithmic Extremism: Examining YouTube's Rabbit Hole of Radicalization", "Time Created": null, "Time Published": "2020-01-27T12:35:14Z", "Duration": null, "Description": "Interview with one of the authors of a widely reported study on YouTube's recommendation engine and where it leads its users.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a4VvcmqnkhY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study (Paper Explained)", "Time Created": null, "Time Published": "2020-08-20T09:46:35Z", "Duration": null, "Description": "ai #research #machinelearning Online Reinforcement Learning is a flourishing field with countless methods for practitioners to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DLq1DUcMh1Q", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "A bio-inspired bistable recurrent cell allows for long-lasting memory (Paper Explained)", "Time Created": null, "Time Published": "2020-06-15T14:13:34Z", "Duration": null, "Description": "Even though LSTMs and GRUs solve the vanishing and exploding gradient problems, they have trouble learning to remember ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eROy3BrqEVk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] AI predicts race from X-Ray | Google kills HealthStreams | Boosting Search with MuZero", "Time Created": null, "Time Published": "2021-09-10T15:18:44Z", "Duration": null, "Description": "mlnews #schmidhuber #muzero Your regular updates on what's happening in the ML world! OUTLINE: 0:00 - Intro 0:15 - Sponsor: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GwItCHOifG8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I'M TAKING A BREAK... (Channel Update July 2020)", "Time Created": null, "Time Published": "2020-07-12T15:10:29Z", "Duration": null, "Description": "Past, Present & Future of this Channel. OUTLINE: 0:00 - I'm going on a break 0:20 - Channel Stats 1:20 - Other Platforms 4:20 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tfYm4zcAnW0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "100K Subs AMA (Ask Me Anything)", "Time Created": null, "Time Published": "2021-09-26T17:50:18Z", "Duration": null, "Description": "Links: TabNine Code Completion (Referral): http://bit.ly/tabnine-yannick YouTube: https://www.youtube.com/c/yannickilcher ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4GKCxJQSw-g", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search (Paper Explained)", "Time Created": null, "Time Published": "2020-06-06T13:56:12Z", "Duration": null, "Description": "Neural Architecture Search is usually prohibitively expensive in both time and resources to be useful. A search strategy has to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-0ce136MdsA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Machine Learning Holidays Live Stream", "Time Created": null, "Time Published": "2021-12-27T14:18:58Z", "Duration": null, "Description": "Chatting & Coding.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tX1OolVxDzs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] Plagiarism Case w/ Plot Twist | CLIP for video surveillance | OpenAI summarizes books", "Time Created": null, "Time Published": "2021-09-29T13:47:40Z", "Duration": null, "Description": "plagiarism #surveillance #schmidhuber Your Mondaily updates of what's going in the world of Machine Learning. OUTLINE: 0:00 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "56GW1IlWgMg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Learning model-based planning from scratch", "Time Created": null, "Time Published": "2017-08-09T06:02:41Z", "Duration": null, "Description": "https://arxiv.org/abs/1707.06170 Abstract: Conventional wisdom holds that model-based planning is a powerful approach to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pZyxlf6l0N8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Thinking While Moving: Deep Reinforcement Learning with Concurrent Control", "Time Created": null, "Time Published": "2020-04-23T13:26:07Z", "Duration": null, "Description": "Classic RL \"stops\" the world whenever the Agent computes a new action. This paper considers a more realistic scenario where ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hkw-WDBipgo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Talking to companies at ICML19", "Time Created": null, "Time Published": "2019-06-13T07:13:32Z", "Duration": null, "Description": "A short rant on sponsor companies at ICML and how to talk to them.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "smxwT82o40Y", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Active Dendrites avoid catastrophic forgetting - Interview with the Authors", "Time Created": null, "Time Published": "2022-03-20T09:23:17Z", "Duration": null, "Description": "multitasklearning #biology #neuralnetworks This is an interview with the paper's authors: Abhiram Iyer, Karan Grewal, and Akash ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "EA96xh9qog0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "I'm at ICML19 :)", "Time Created": null, "Time Published": "2019-06-10T18:20:07Z", "Duration": null, "Description": "Short intro to the International Conference on Machine Learning in Long Beach, CA. I'll be making some updates from the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3Tqp_B2G6u0", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Blockwise Parallel Decoding for Deep Autoregressive Models", "Time Created": null, "Time Published": "2019-05-06T09:46:52Z", "Duration": null, "Description": "https://arxiv.org/abs/1811.03115 Abstract: Deep autoregressive sequence-to-sequence models have demonstrated impressive ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3jT1qJ8ETzk", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "SupSup: Supermasks in Superposition (Paper Explained)", "Time Created": null, "Time Published": "2020-07-07T17:16:53Z", "Duration": null, "Description": "Supermasks are binary masks of a randomly initialized neural network that result in the masked network performing well on a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XdpF9ZixIbI", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Can we Contain Covid-19 without Locking-down the Economy?", "Time Created": null, "Time Published": "2020-04-02T09:30:19Z", "Duration": null, "Description": "My thoughts on the let-the-young-get-infected argument.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OUCwujwE7bA", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied Agents (+Author)", "Time Created": null, "Time Published": "2022-02-08T21:13:05Z", "Duration": null, "Description": "gpt3 #embodied #planning In this video: Paper explanation, followed by first author interview with Wenlong Huang.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "z4lAlVRwbrc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - Improving Intrinsic Exploration with Language Abstractions", "Time Created": null, "Time Published": "2022-04-02T22:38:55Z", "Duration": null, "Description": "reinforcementlearning #ai #explained This is an interview with Jesse Mu, first author of the paper. Original Paper Review: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l8JeokY5NsU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Conversation about Population-Based Methods (Re-upload)", "Time Created": null, "Time Published": "2019-07-05T08:04:42Z", "Duration": null, "Description": "Being interviewed by Connor Shorten of Henry AI Labs (https://www.youtube.com/channel/UCHB9VepY6kYvZjj0Bgxnpbw) on the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oRkhACMRy7Y", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "ML News Live! (Dec 30, 2021) Anonymous user RIPS Tensorflw | AI prosecutors rising | Penny Challenge", "Time Created": null, "Time Published": "2021-12-30T16:24:46Z", "Duration": null, "Description": "mlnews #live #tensorflow The greatest news, now fully live! Sponsor: Weights & Biases https://wandb.me/yannic References: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "plK2WVdLTOY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Extracting Training Data from Large Language Models (Paper Explained)", "Time Created": null, "Time Published": "2020-12-26T19:42:56Z", "Duration": null, "Description": "ai #privacy #tech This paper demonstrates a method to extract verbatim pieces of the training data from a trained language model.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AR3W-nfcDe4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Auditing Radicalization Pathways on YouTube", "Time Created": null, "Time Published": "2019-08-28T17:46:35Z", "Duration": null, "Description": "This paper claims that there is a radicalization pipeline on YouTube pushing people towards the Alt-Right, backing up their claims ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "F5mxzvgl_oU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "S.H.E. - Search. Human. Equalizer.", "Time Created": null, "Time Published": "2019-05-09T10:33:31Z", "Duration": null, "Description": "Short opinion on Pantene's tool to de-bias Google search results.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Jqvb7jp4Nm8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Addendum for Supermasks in Superposition: A Closer Look (Paper Explained)", "Time Created": null, "Time Published": "2020-07-08T13:36:15Z", "Duration": null, "Description": "I take a closer look at \"Supermasks in Superposition\" after I've already done a video on it. Specifically, I look at: 1. The intuition ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pPBqM4CKjUU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Discriminating Systems - Gender, Race, and Power in AI", "Time Created": null, "Time Published": "2019-04-27T19:49:27Z", "Duration": null, "Description": "TL;DR: - There exists both an unequal representation of people in the AI workforce as well as examples of societal bias in AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "V79rRI05Lj4", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Set Distribution Networks: a Generative Model for Sets of Images (Paper Explained)", "Time Created": null, "Time Published": "2020-06-29T12:58:05Z", "Duration": null, "Description": "We've become very good at making generative models for images and classes of images, but not yet of sets of images, especially ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RrBapqCPnmE", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML Coding Tips] Separate Computation & Plotting using locals", "Time Created": null, "Time Published": "2020-05-01T17:22:06Z", "Duration": null, "Description": "Here's a lazy way to separate computation and subsequent analysis in a notebook without the overhead of manually saving local ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "R07CVhWbAXc", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "2M All-In into $5 Pot! WWYD? Daniel Negreanu's No-Limit Hold'em Challenge! (Poker Hand Analysis)", "Time Created": null, "Time Published": "2020-12-13T18:15:43Z", "Duration": null, "Description": "ai #technology #poker Daniel Negreanu posted a set of very interesting No-Limit Hold'em situations on Twitter. I try to analyze ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "klPuEHCKG9M", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Evolving Normalization-Activation Layers", "Time Created": null, "Time Published": "2020-04-09T11:10:44Z", "Duration": null, "Description": "Normalization and activation layers have seen a long history of hand-crafted variants with various results. This paper proposes an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cvkeWwDQr0A", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "JOIN ME for the NeurIPS 2020 Flatland Multi-Agent RL Challenge!", "Time Created": null, "Time Published": "2020-06-08T14:48:00Z", "Duration": null, "Description": "Join me to solve the NeurIPS 2020 challenge on multi-agent reinforcement learning in the flatland environment. This challenge ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ifBI2jTaAEo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Celebrating 100k Subscribers! (w/ Channel Statistics)", "Time Created": null, "Time Published": "2021-09-14T07:36:41Z", "Duration": null, "Description": "yannickilcher #machinelearning #100k OUTLINE: 0:00 - 100k! 1:00 - Announcements & Thanks 3:55 - Channel Statistics Links: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "InhMx1h0N40", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "N\u00dcWA: Visual Synthesis Pre-training for Neural visUal World creAtion (ML Research Paper Explained)", "Time Created": null, "Time Published": "2021-12-08T18:54:58Z", "Duration": null, "Description": "nuwa #microsoft #generative N\u00dcWA is a unifying architecture that can ingest text, images, and videos and brings all of them into a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gch94ttuy5s", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Underspecification Presents Challenges for Credibility in Modern Machine Learning (Paper Explained)", "Time Created": null, "Time Published": "2020-11-10T21:48:01Z", "Duration": null, "Description": "ai #research #machinelearning Deep Learning models are often overparameterized and have many degrees of freedom, which ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "O1b0cbgpRBw", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess (Paper Explained)", "Time Created": null, "Time Published": "2020-09-13T19:56:31Z", "Duration": null, "Description": "ai #chess #alphazero Chess is a very old game and both its rules and theory have evolved over thousands of years in the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zt_R85Ife_U", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[Trash] Automated Inference on Criminality using Face Images", "Time Created": null, "Time Published": "2020-05-14T14:07:15Z", "Duration": null, "Description": "This paper sets out to build a classifier to distinguish criminals from non-criminals using nothing but a face picture. I explore why ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tDk10VTHwNo", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] CVPR bans social media paper promotion | AI restores Rembrandt | GPU prices down", "Time Created": null, "Time Published": "2021-06-30T14:26:12Z", "Duration": null, "Description": "cvpr #socialmedia #machinelearning In this week's ML news we look at CVPR's controversial action to ban paper promotions on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kU-tWy_wr78", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Fast and Slow Learning of Recurrent Independent Mechanisms (Machine Learning Paper Explained)", "Time Created": null, "Time Published": "2021-05-29T16:35:08Z", "Duration": null, "Description": "metarim #deeprl #catastrophicforgetting Reinforcement Learning is very tricky in environments where the objective shifts over time ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wcHQ3IutSJg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[News] The NeurIPS Broader Impact Statement", "Time Created": null, "Time Published": "2020-05-23T15:27:05Z", "Duration": null, "Description": "For the first time, all authors submitting to the NeurIPS conference are forced to write a statement about the broader impact of their ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XvDzZwoQFcU", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[News] Facebook's Real-Time TTS system runs on CPUs only!", "Time Created": null, "Time Published": "2020-05-16T13:57:10Z", "Duration": null, "Description": "Facebook AI's new Text-To-Speech system is able to create 1 second of speech in as little as 500ms, making it real-time. What's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4xklF7PZ-BY", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "[ML News] MMO Game destroys GPUs | OpenAI quits Robotics | Today w/ guest host Sanyam Bhutani", "Time Created": null, "Time Published": "2021-08-02T15:02:35Z", "Duration": null, "Description": "chai #mlnews #nvidia Follow Saynam here: YouTube: https://www.youtube.com/c/ChaiTimeDataScience Twitter: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WvTU-y8HyDg", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Machine Learning Holiday Live Stream", "Time Created": null, "Time Published": "2021-12-26T17:09:53Z", "Duration": null, "Description": "Just chilling, coding, talking.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cO1nSnsH_CQ", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Listening to You! - Channel Update (Author Interviews)", "Time Created": null, "Time Published": "2022-02-21T18:36:59Z", "Duration": null, "Description": "mlnews #kilcher #withtheauthors Many of you have given me feedback on what you did and didn't like about the recent \"with the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TFiZYA_JfJs", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Population-Based Search and Open-Ended Algorithms", "Time Created": null, "Time Published": "2019-06-12T22:33:17Z", "Duration": null, "Description": "Comments on the ICML2019 tutorial on population-based search and open-ended learning.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3ks2gpqAKY8", "Channel ID": "UCZHmQk67mSJgfCCTn7xBfew", "Title": "Author Interview - Memory-assisted prompt editing to improve GPT-3 after deployment", "Time Created": null, "Time Published": "2022-03-29T15:09:06Z", "Duration": null, "Description": "nlp #gpt3 #prompt This is an interview with the authors of this work, Aman Madaan and Niket Tandon. Large language models ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Lv1fv-HmkQo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Flask Tutorial Web Development with Python 1 - Intro", "Time Created": null, "Time Published": "2015-03-20T15:08:24Z", "Duration": null, "Description": "Digital Ocean Hosting: https://www.digitalocean.com/?refcode=d1c4c6e66979 Linode Hosting: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Z81JW1NTsO8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Matplotlib Tutorial 5 - stack plots", "Time Created": null, "Time Published": "2015-07-12T02:05:04Z", "Duration": null, "Description": "In this Matplotlib data visualization tutorial, we cover how to create stack plots. The idea of stack plots is to show \"parts to the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iv5m0c-8Opc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Tuples, Strings, Loops - Python 3 Programming Tutorial p.2", "Time Created": null, "Time Published": "2018-10-28T15:58:21Z", "Duration": null, "Description": "Getting familiar with some basic Python principles like tuples, strings, and loops as we see how simple Python really is to both ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "r9LtArXOYjk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 Programming Tutorial - Global and Local Variables", "Time Created": null, "Time Published": "2014-04-20T23:14:02Z", "Duration": null, "Description": "Welcome to another python 3 basics video, in this video we're going to now discuss the concept of global and local variables.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jSs58VZVLw8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 programming tutorial: While Loop", "Time Created": null, "Time Published": "2014-01-22T05:32:46Z", "Duration": null, "Description": "The two distinctive loops we have in Python 3 logic are the \"for loop\" and the \"while loop.\" Both of them achieve very similar results ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CGRKqnoQGgM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 Programming Tutorial - Function Parameters", "Time Created": null, "Time Published": "2014-04-20T23:13:35Z", "Duration": null, "Description": "The idea of function parameters in Python is to allow a programmer who is using that function, define variables dynamically within ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2Tw39kZIbhs", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python Pickle Module for saving objects (serialization)", "Time Created": null, "Time Published": "2015-05-22T16:02:04Z", "Duration": null, "Description": "This Python programming tutorial covers how to pickle objects in Python. The pickle module implements binary protocols for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "42MBMSOZgD4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 Programming Tutorial: If Elif Else", "Time Created": null, "Time Published": "2014-01-23T20:08:54Z", "Duration": null, "Description": "Now we bring the in \"elif\" statement. The elif allows us to tie multiple if statements together as we might have intended to before ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Siyg1Wn5VDs", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Building Search Word Database - Data Analysis of Google Tracking Takeout p.1", "Time Created": null, "Time Published": "2019-05-06T13:43:12Z", "Duration": null, "Description": "In these videos, we're going to be analyzing some of the data that we can download on ourselves that Google tracks on us.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "G3PvTWRIhZA", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Introduction - Go Lang Practical Programming Tutorial p.1", "Time Created": null, "Time Published": "2017-10-21T17:58:19Z", "Duration": null, "Description": "Hello and welcome to a Go Language programming tutorial. In this series, we're going to cover setting up and the basics of using ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AOeRbuwCd-Y", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "My Biggest Challenge With Programming (Q&A #11)", "Time Created": null, "Time Published": "2019-06-30T18:00:52Z", "Duration": null, "Description": "In this Q&A video, we'll be discussing various programming hardships and how I got into machine learning. Channel membership: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qf0sfRZ0hHc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 Programming Tutorial: If Else", "Time Created": null, "Time Published": "2014-01-23T20:08:45Z", "Duration": null, "Description": "The If-Else statement is designed to build on the if statement's logic. Here, we ask if something is the case, and, if it is we do ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Wo5dMEP_BbI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.1 Intro and Neuron Code", "Time Created": null, "Time Published": "2020-04-11T13:49:09Z", "Duration": null, "Description": "Building neural networks from scratch in Python introduction. Neural Networks from Scratch book: https://nnfs.io Playlist for this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "S11VFAMEs6E", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Channels - Go Lang Practical  Programming Tutorial p.22", "Time Created": null, "Time Published": "2017-11-12T15:09:07Z", "Duration": null, "Description": "We use Go Channels to connect concurrent goroutines, in order to send and receive values between them, using the channel ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3fsvqo9pQyg", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Structs - Go Lang Practical Programming Tutorial p.6", "Time Created": null, "Time Published": "2017-10-23T13:16:45Z", "Duration": null, "Description": "In the programming language of Go, there are no Classes. Instead, we can create custom types called Structs, which we then ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "q59wap1ELQ4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "A. I. Learns to Play Starcraft 2 (Reinforcement Learning)", "Time Created": null, "Time Published": "2022-04-23T15:05:05Z", "Duration": null, "Description": "Tinkering with reinforcement learning via Stable Baselines 3 and Starcraft 2. Code and model: https://github.com/Sentdex/SC2RL ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wQ8BIBpya2k", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Deep Learning with Python, TensorFlow, and Keras tutorial", "Time Created": null, "Time Published": "2018-08-11T14:17:31Z", "Duration": null, "Description": "An updated deep learning introduction using Python, TensorFlow, and Keras. Text-tutorial and notes: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IDqQIDL3LKg", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Remote Access with SSH and Remote Desktop - Raspberry Pi and Python tutorials p.3", "Time Created": null, "Time Published": "2017-04-03T13:15:24Z", "Duration": null, "Description": "In this Raspberry Pi tutorial, we're going to cover how we can remotely access our Raspberry Pi, both with SSH and with a remote ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DF_44sWnAsk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Application Structure - PyQt with Python GUI  Programming tutorial 2", "Time Created": null, "Time Published": "2015-05-26T13:17:08Z", "Duration": null, "Description": "In this PyQT4 tutorial video, we cover how to structure a PyQT application in your code, using object oriented programming, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MF4NWqArewo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Detecting collisions - Intermediate Python Programming p.20", "Time Created": null, "Time Published": "2016-12-06T14:37:13Z", "Duration": null, "Description": "Now that we've got handling for the \"+\" operator, we need to devise a way to actually detect when we need to use it. In this tutorial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Zg7GK759ZzA", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Goroutines - Go Lang Practical  Programming Tutorial p.18", "Time Created": null, "Time Published": "2017-11-09T16:13:05Z", "Duration": null, "Description": "Welcome everyone to part 18 of the Go Language programming tutorial series, where we'll be talking about concurrency in Go.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TEWy9vZcxW4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.4 Batches, Layers, and Objects", "Time Created": null, "Time Published": "2020-05-01T14:07:12Z", "Duration": null, "Description": "Neural Networks from Scratch book: https://nnfs.io NNFSiX Github: https://github.com/Sentdex/NNfSiX Playlist for this series: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OwakEEY_DFw", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Pointers - Go Lang Practical Programming Tutorial p.4", "Time Created": null, "Time Published": "2017-10-21T17:59:01Z", "Duration": null, "Description": "Welcome to part 4 of the Go programming tutorial series. In the previous tutorial, we covered some function basics. Now, we're ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BVWmstt0AWM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Home Lab Build - P.2 - Rack has evolved!", "Time Created": null, "Time Published": "2022-07-01T14:40:12Z", "Duration": null, "Description": "Quite a few changes to the server rack, starting with a patch panel and another ethernet switch. From here, I've mounted a KVM ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZoWgzG_r2qo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "List comprehension and generator expressions - Intermediate Python Programming p.4", "Time Created": null, "Time Published": "2016-11-04T13:31:25Z", "Duration": null, "Description": "Welcome to part 4 of the intermediate Python programming tutorial series. In this part, we're going to talk about list comprehension ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mA5nwGoRAOo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Support Vector Machine Intro and Application  - Practical Machine Learning Tutorial with Python p.20", "Time Created": null, "Time Published": "2016-05-13T16:20:36Z", "Duration": null, "Description": "In this tutorial, we introduce the theory of the Support Vector Machine (SVM), which is a classification learning algorithm for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Lbfe3-v7yE0", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Sockets Tutorial with Python 3 part 1 - sending and receiving data", "Time Created": null, "Time Published": "2019-03-11T14:22:40Z", "Duration": null, "Description": "Welcome to a tutorial on sockets with Python 3. We have a lot to cover, so let's just jump right in. The socket library is a part of the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PDNt07UePvk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Github Copilot: Good or Bad?", "Time Created": null, "Time Published": "2021-11-13T15:56:26Z", "Duration": null, "Description": "My thoughts and some examples of Github Copilot. Neural Networks from Scratch book: https://nnfs.io Channel membership: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rTyEMsD-NNM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Why I use a Standing Desk", "Time Created": null, "Time Published": "2019-06-03T16:03:56Z", "Duration": null, "Description": "I get questions all the time about my desk and figured I might as well have a video to point people towards to make my life easier!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "levekYbxauw", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.8 Implementing Loss", "Time Created": null, "Time Published": "2021-06-05T14:27:57Z", "Duration": null, "Description": "Implementing categorical cross entropy loss in our neural network framework. NNFS series playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rISOsUaTrO4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Naive Bayes - Natural Language Processing With Python and NLTK p.13", "Time Created": null, "Time Published": "2015-05-14T15:10:55Z", "Duration": null, "Description": "The algorithm of choice, at least at a basic level, for text analysis is often the Naive Bayes classifier. Part of the reason for this is ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xtXexPSfcZg", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Python 3 Programming Tutorial - For loop", "Time Created": null, "Time Published": "2014-01-22T05:45:00Z", "Duration": null, "Description": "The next loop is the For loop. The idea of the for loop is to \"iterate\" through something. For each thing in that something, it will do a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RpseX2ylEuw", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Introduction and Parts - Raspberry Pi and Python tutorials p.1", "Time Created": null, "Time Published": "2017-04-03T13:15:06Z", "Duration": null, "Description": "Welcome to a series on the Raspberry Pi. One of the most common questions I see about the Raspberry Pi is \"What do I do with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "V59bYfIomVk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Regression How it Works - Practical Machine Learning Tutorial with Python p.7", "Time Created": null, "Time Published": "2016-04-16T13:54:18Z", "Duration": null, "Description": "Welcome to the seventh part of our machine learning regression tutorial within our Machine Learning with Python tutorial series.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aVDkuViaJfY", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Defer - Go Lang Practical  Programming Tutorial p.20", "Time Created": null, "Time Published": "2017-11-11T14:07:07Z", "Duration": null, "Description": "Welcome to part 20 of the Go programming tutorial, where we will be introducing the defer statement and its use in Go. The idea of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6e6NbNegChU", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Corner Detection - OpenCV with Python for Image and Video Analysis 13", "Time Created": null, "Time Published": "2016-01-08T00:31:44Z", "Duration": null, "Description": "Welcome to a corner detection with OpenCV and Python tutorial. The purpose of detecting corners is to track things like motion, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rPCeCPT-f28", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Decorators - Intermediate Python Programming p.18", "Time Created": null, "Time Published": "2016-11-29T14:28:08Z", "Duration": null, "Description": "Welcome to part 18 of the intermediate Python programming tutorial series. In this tutorial, we are going to be discussing ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WM1z8soch0Q", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Sockets Tutorial with Python 3 part 3 - sending and receiving Python Objects w/ Pickle", "Time Created": null, "Time Published": "2019-03-13T13:52:35Z", "Duration": null, "Description": "Welcome to part 3 of the sockets tutorial with Python. We've learned how to send and receive string data via sockets, and now I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "za5s7RB_VLw", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Pickling and Scaling - Practical Machine Learning Tutorial with Python p.6", "Time Created": null, "Time Published": "2016-04-15T02:24:09Z", "Duration": null, "Description": "In the previous Machine Learning with Python tutorial we finished up making a forecast of stock prices using regression, and then ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ixathu7U-LQ", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Building our Neural Network - Deep Learning and Neural Networks with Python and Pytorch p.3", "Time Created": null, "Time Published": "2019-09-25T14:19:43Z", "Duration": null, "Description": "In this tutorial, we're going to focus on actually creating a neural network Text-based tutorials and sample code: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZmYPzESC5YY", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Matplotlib Tutorial 16 - Live graphs", "Time Created": null, "Time Published": "2015-07-12T02:06:17Z", "Duration": null, "Description": "In this Matplotlib tutorial, we're going to cover how to create live updating graphs that can update their plots live as the data-source ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-bTuXf1xM_8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Adding a tutorial option - Tkinter tutorial Python 3.4 part 19", "Time Created": null, "Time Published": "2014-12-03T15:11:56Z", "Duration": null, "Description": "Tkinter GUI Tutorial Playlist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk In this tkinter ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2R0kGTuYmVI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Exploring an AI\u2019s Imagination (Stable Diffusion and MidJourney)", "Time Created": null, "Time Published": "2022-09-03T13:54:26Z", "Duration": null, "Description": "Exploring a couple of the latest text to image generators that you can begin using right now, Stable Diffusion and MidJourney.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "i3o4G4bmqPc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Methods - Value Receivers - Go Lang Practical Programming Tutorial p.7", "Time Created": null, "Time Published": "2017-10-23T13:16:48Z", "Duration": null, "Description": "Welcome to part 7 of the Go programming tutorial series. We've been talking about structs, and we saw how to create a struct in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cJtdb-vPxBo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Kivy with Python tutorial Part 2 - Widgets and Labels", "Time Created": null, "Time Published": "2015-02-19T14:43:31Z", "Duration": null, "Description": "In this Kivy application development tutorial, we cover widgets and labels, as well as diving into some of the extensive Kivy ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lGLto9Xd7bU", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.2 Coding a Layer", "Time Created": null, "Time Published": "2020-04-17T13:57:47Z", "Duration": null, "Description": "Expanding from a single neuron with 3 inputs to a layer of neurons with 4 inputs. Neural Networks from Scratch book: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0hrrycamKPM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Exchange choice change - Tkinter tutorial Python 3.4 part 20", "Time Created": null, "Time Published": "2014-12-04T17:17:26Z", "Duration": null, "Description": "Tkinter GUI TutorialPlaylist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk This Tkinter GUI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "uoHVztKY6S4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Lemmatizing - Natural Language Processing With Python and NLTK p.8", "Time Created": null, "Time Published": "2015-05-07T14:18:53Z", "Duration": null, "Description": "A very similar operation to stemming is called lemmatizing. The major difference between these is, as you saw earlier, stemming ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WLo5Rgvj6qo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "GPIO Basics with LED light - Raspberry Pi and Python tutorials p.6", "Time Created": null, "Time Published": "2017-04-03T13:15:30Z", "Duration": null, "Description": "In this Raspberry Pi tutorial, we're going to be introducing and using the GPIO (General Purpose Input Output) pins on our boards.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oVp1vrfL_w4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Why Python 3? Python 2 vs Python 3", "Time Created": null, "Time Published": "2014-01-22T01:02:58Z", "Duration": null, "Description": "This video covers why one is encouraged to try Python 3. This is whether you are a complete noob to Python and programming, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aZltBzPUPKI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Building a Quadcopter p.2 - Parts", "Time Created": null, "Time Published": "2016-03-08T15:18:35Z", "Duration": null, "Description": "Parts list: https://pythonprogramming.net/quadcopter-parts-tutorial/ Hello and welcome to the second tutorial covering how to build ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sh-MQboWJug", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "A Deep Dream of a Neural Network", "Time Created": null, "Time Published": "2018-03-31T14:02:40Z", "Duration": null, "Description": "A deep dream with TensorFlow's inception model. It's a deep dream through the inception v3 model's layers that's trained on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7Wq-QmMT4gM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Convolutional Neural Networks Basics - Deep Learning withTensorFlow 12", "Time Created": null, "Time Published": "2016-09-19T13:09:40Z", "Duration": null, "Description": "In this tutorial, we cover the basics of the Convolutional Neural Network (CNN) in terms of how the network works and how the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HRKfVjCB3lM", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Goroutine Synchronization - Go Lang Practical  Programming Tutorial p.19", "Time Created": null, "Time Published": "2017-11-10T13:59:13Z", "Duration": null, "Description": "Welcome everyone to part 19 of the Go Language programming tutorial series, where we've been covering concurrency in Go, but ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3ERPpzrDkVg", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Mean Shift Intro - Practical Machine Learning Tutorial with Python p.39", "Time Created": null, "Time Published": "2016-06-29T14:44:24Z", "Duration": null, "Description": "Mean Shift is very similar to the K-Means algorithm, except for one very important factor: you do not need to specify the number of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8sCQQlqeOKY", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Game Development in Python 3 With PyGame - 20 - Sounds and Music", "Time Created": null, "Time Published": "2014-10-30T13:35:55Z", "Duration": null, "Description": "See http://pythonprogramming.net for sample code PyGame with Python 3 Playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oP95o2cUbTI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Looping - Go Lang Practical Programming Tutorial p.12", "Time Created": null, "Time Published": "2017-10-28T17:51:02Z", "Duration": null, "Description": "Welcome to part 12 of the Go programming tutorial series, where we're going to cover looping/iterating in Go. Leading up to this, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "T-Sc-uq4n5c", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Flask Tutorial Web Development with Python 14 - Connecting to database", "Time Created": null, "Time Published": "2015-03-30T02:10:21Z", "Duration": null, "Description": "Welcome to part 14 of our Flask web development tutorial, in this video we discuss how to connect to our MySQL database using ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-vVskDsHcVc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Words as Features for Learning - Natural Language Processing With Python and NLTK p.12", "Time Created": null, "Time Published": "2015-05-13T12:53:42Z", "Duration": null, "Description": "For our text classification, we have to find some way to \"describe\" bits of data, which are labeled as either positive or negative for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BqgTU7_cBnk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Analyzing Models with TensorBoard - Deep Learning with Python, TensorFlow and Keras p.4", "Time Created": null, "Time Published": "2018-08-24T14:24:31Z", "Duration": null, "Description": "Welcome to part 4 of the deep learning basics with Python, TensorFlow, and Keras tutorial series. In this part, what we're going to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aXxIjeGR6po", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Models - Django Web Development with Python p.2", "Time Created": null, "Time Published": "2019-01-22T13:48:47Z", "Duration": null, "Description": "Welcome to Part 2 of the web development with Python and Django tutorial series. In this tutorial, we're going to introduce the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Y6cir7P3YUk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Functions with Parameters with Tkinter GUI buttons - Tkinter tutorial Python 3.4 p. 3", "Time Created": null, "Time Published": "2014-10-27T21:05:18Z", "Duration": null, "Description": "Tkinter GUI TutorialPlaylist: http://www.youtube.com/playlist?list=PLQVvvaa0QuDclKx-QpC9wntnURXVJqLyk In this Tkinter with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cu7t-GqtTRw", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Running locally and getting surrounding data - Halite III coding competition p.2", "Time Created": null, "Time Published": "2018-10-18T13:53:00Z", "Duration": null, "Description": "Text tutorials and sample code: coming soon(tm) Discord: https://discord.gg/sentdex Support the content: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6_GXTbTL9Uc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Coding Adventure with Kaggle and Lux AI", "Time Created": null, "Time Published": "2021-09-26T16:25:13Z", "Duration": null, "Description": "Follow along on my journey of coding a Python AI agent for the Lux AI Kaggle competition. Lux Competition on Kaggle: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WbTOutpwPHs", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Matplotlib Tutorial 4 - Scatter Plots", "Time Created": null, "Time Published": "2015-07-12T02:04:58Z", "Duration": null, "Description": "Next up, we cover scatter plots! The idea of scatter plots is usually to compare two variables, or three if you are plotting in 3 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-fgYp74SNtk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "R Squared Theory - Practical Machine Learning Tutorial with Python p.10", "Time Created": null, "Time Published": "2016-04-21T18:11:14Z", "Duration": null, "Description": "Welcome to the 10th part of our of our machine learning regression tutorial within our Machine Learning with Python tutorial series ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BzcBsTou0C0", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Introduction - Deep Learning and Neural Networks with Python and Pytorch p.1", "Time Created": null, "Time Published": "2019-09-23T13:57:15Z", "Duration": null, "Description": "Hello and welcome to a deep learning with Python and Pytorch tutorial series, starting from the basics. Text-based tutorials and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yZgaxg0JzcU", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Bitcoin Protocol Tutorial #9 - Reclaiming Disk Space", "Time Created": null, "Time Published": "2014-02-08T00:34:04Z", "Duration": null, "Description": "Bitcoin Protocol Paper Playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BSpXCRTOLJA", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Recurrent Neural Networks (RNN) - Deep Learning w/ Python, TensorFlow & Keras p.7", "Time Created": null, "Time Published": "2018-09-07T14:32:02Z", "Duration": null, "Description": "In this part we're going to be covering recurrent neural networks. The idea of a recurrent neural network is that sequences and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "275_oeBw3vY", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Creating Stable Diffusion Interpolation Videos", "Time Created": null, "Time Published": "2022-09-16T15:19:34Z", "Duration": null, "Description": "GTC signup: https://nvda.ws/3BQvmCP Stable Diffusion Videos Github: https://github.com/nateraw/stable-diffusion-videos Gist for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dvOnYLDg8_Y", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Creating a Chatbot with Deep Learning, Python, and TensorFlow p.1", "Time Created": null, "Time Published": "2017-11-24T15:26:34Z", "Duration": null, "Description": "In this tutorial series we build a Chatbot with TensorFlow's sequence to sequence library and by building a massive database from ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qk1IVs5B1GI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Camera Module - Raspberry Pi and Python tutorials p.5", "Time Created": null, "Time Published": "2017-04-03T13:15:30Z", "Duration": null, "Description": "Welcome to part 5 of the Raspberry Pi tutorial series, in this tutorial and the next few, we'll be introducing some of the sensors that ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WFm1RZCVShU", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "AI-Based Game Engines with GameGAN research paper", "Time Created": null, "Time Published": "2020-05-22T13:13:54Z", "Duration": null, "Description": "Learning to Simulate Dynamic Environments with GameGAN: https://nv-tlabs.github.io/gameGAN/ Link to paper: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iRrySp4VoPs", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Jetson Nano 2GB from NVIDIA", "Time Created": null, "Time Published": "2020-10-14T15:30:53Z", "Duration": null, "Description": "Get it here: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-nano/education-projects/ Channel ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yMk_XtIEzH8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Q Learning Intro/Table - Reinforcement Learning p.1", "Time Created": null, "Time Published": "2019-05-30T13:26:14Z", "Duration": null, "Description": "Welcome to a reinforcement learning tutorial. In this part, we're going to focus on Q-Learning. Q-Learning is a model-free form of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "j-3vuBynnOE", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Loading in your own data - Deep Learning basics with Python, TensorFlow and Keras p.2", "Time Created": null, "Time Published": "2018-08-18T13:50:58Z", "Duration": null, "Description": "Welcome to a tutorial where we'll be discussing how to load in our own outside datasets, which comes with all sorts of challenges!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "COlbP62-B-U", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Intro - TensorFlow Object Detection API Tutorial p.1", "Time Created": null, "Time Published": "2017-08-21T14:19:31Z", "Duration": null, "Description": "Hello and welcome to a miniseries and introduction to the TensorFlow Object Detection API. This API can be used to detect, with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "QyhqzaMiFxk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Matplotlib Tutorial 7 - loading data from files", "Time Created": null, "Time Published": "2015-07-12T02:05:14Z", "Duration": null, "Description": "Many times, people want to graph data from a file. There are many types of files, and many ways you may extract data from a file to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kqJ8WYQu68w", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Distance Sensor GPIO cont'd - Raspberry Pi and Python tutorials p.7", "Time Created": null, "Time Published": "2017-04-05T00:52:55Z", "Duration": null, "Description": "In this Raspberry Pi tutorial, we're going to introduce a new sensor, the HC-SR04 ultrasonic distance sensor, along with handling ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eXBD2bB9-RA", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Introduction to Python 3 Programming Tutorial", "Time Created": null, "Time Published": "2018-10-27T15:58:41Z", "Duration": null, "Description": "Downloading and installing Python 3, along with an editor and writing our very first, though super basic, program! Playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Q8KtQ3uM1tk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Bitcoin Protocol Tutorial #8: Incentive", "Time Created": null, "Time Published": "2014-02-06T21:02:35Z", "Duration": null, "Description": "Bitcoin Protocol Paper Playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dEXPMQXoiLc", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.7 Calculating Loss with Categorical Cross-Entropy", "Time Created": null, "Time Published": "2021-01-23T15:47:17Z", "Duration": null, "Description": "In order to do backpropagation and optimization, we need to have some measure of how wrong the model is. For this, we use a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-QmdZ7821wA", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Simple Web App - Go Lang Practical Programming Tutorial p.5", "Time Created": null, "Time Published": "2017-10-21T17:59:06Z", "Duration": null, "Description": "Welcome to part 5 of the Go programming tutorial series, where we'll poke around a bit with the built-in web server with the Go ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WvoLTXIjBYU", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Convolutional Neural Networks - Deep Learning basics with Python, TensorFlow and Keras p.3", "Time Created": null, "Time Published": "2018-08-19T13:34:14Z", "Duration": null, "Description": "Welcome to a tutorial where we'll be discussing Convolutional Neural Networks (Convnets and CNNs), using one to classify dogs ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xqg5S-GrrDQ", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Why Kernels - Practical Machine Learning Tutorial with Python p.30", "Time Created": null, "Time Published": "2016-05-30T12:53:02Z", "Duration": null, "Description": "Once we've determined that we can use Kernels, the next question is of course why would we bother using kernels when we can ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IsyyRKbFi7w", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Object Oriented Programming in js - JavaScript Programming Basics p.5", "Time Created": null, "Time Published": "2019-05-20T13:26:47Z", "Duration": null, "Description": "Greetings and welcome to part 5 of the JavaScript basics! In this tutorial, we're going to dive into Object Oriented Programming ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "K_Ac1Ko8-p8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Bitcoin Protocol: Proof of Work shown in Python Code", "Time Created": null, "Time Published": "2014-02-04T18:24:47Z", "Duration": null, "Description": "Bitcoin Protocol Paper Playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ha7TP11H0EI", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Kivy with Python tutorial Part 5 - Dynamic Resizable Placement", "Time Created": null, "Time Published": "2015-02-23T00:38:05Z", "Duration": null, "Description": "In this Kivy application development tutorial, we cover how to code dynamic positions for things like widgets and buttons, this way ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sNHiM0DoEAg", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch (NNFS) in Print!", "Time Created": null, "Time Published": "2020-10-28T13:10:02Z", "Duration": null, "Description": "Get the book: https://nnfs.io twitters: twitter.com/sentdex twitter.com/daniel_kukiela Channel membership: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JBME1ZyHiP8", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Intro/basic GUI - PyQt with Python GUI  Programming tutorial", "Time Created": null, "Time Published": "2015-05-25T14:04:07Z", "Duration": null, "Description": "PyQT is a Python wrapper around the QT GUI application development framework. To get PyQT, head to: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3EjtHs_lXnk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "$5 MILLION AI for FREE", "Time Created": null, "Time Published": "2022-08-12T15:18:07Z", "Duration": null, "Description": "Imagine an AI where, all in the same model you could Translate languages, Write code, solve crossword puzzles, Be a chatbot ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NRgfgtzIhBQ", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Introduction and Basics - Python Reddit API Wrapper (PRAW) tutorial p.1", "Time Created": null, "Time Published": "2017-08-07T13:43:29Z", "Duration": null, "Description": "In this tutorial miniseries, we're going to be covering the Python Reddit API Wrapper, PRAW. Reddit is a place for just about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vvC15l4CY1Q", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Optimizing Neural Network Structures with Keras-Tuner", "Time Created": null, "Time Published": "2019-12-21T15:01:42Z", "Duration": null, "Description": "Tuning and optimizing neural networks with the Keras-Tuner package: https://keras-team.github.io/keras-tuner/ Kite AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "txh3TQDwP1g", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.9 Introducing Optimization and derivatives", "Time Created": null, "Time Published": "2021-08-02T22:08:08Z", "Duration": null, "Description": "Introducing the challenge of optimization and the concepts of derivatives NNFS series playlist: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tMrbN67U9d4", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Neural Networks from Scratch - P.3 The Dot Product", "Time Created": null, "Time Published": "2020-04-24T14:27:00Z", "Duration": null, "Description": "Neural Networks from Scratch book: https://nnfs.io NNFSiX Github: https://github.com/Sentdex/NNfSiX Playlist for this series: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XbWhJdQgi7E", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Reinforcement Learning with Stable Baselines 3 - Introduction (P.1)", "Time Created": null, "Time Published": "2022-02-05T15:56:01Z", "Duration": null, "Description": "Welcome to a tutorial series covering how to do reinforcement learning with the Stable Baselines 3 (SB3) package. The objective ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ReakZVh2Xwk", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Save Classifier with Pickle  - Natural Language Processing With Python and NLTK p.14", "Time Created": null, "Time Published": "2015-05-15T15:00:52Z", "Duration": null, "Description": "As you will likely find with any form of data analysis, there is going to be some sort of processing bottleneck, that you repeat over ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "RxZKbEmm7z0", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Kivy with Python tutorial Part 12 - Adding better Navigation", "Time Created": null, "Time Published": "2015-02-27T01:32:22Z", "Duration": null, "Description": "In this Kivy application development tutorial, we cover how to add on top of our previous example with a button that heads back ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SN0VwEt2huo", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "NNFS Update #2: Content done", "Time Created": null, "Time Published": "2020-09-25T17:49:03Z", "Duration": null, "Description": "More info: https://nnfs.io Channel membership: https://www.youtube.com/channel/UCfzlCWGWYyIQ0aLC5w48gBQ/join Discord: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lhMXDqQHf9g", "Channel ID": "UCfzlCWGWYyIQ0aLC5w48gBQ", "Title": "Line Finding with Hough Lines - Python plays Grand Theft Auto 5 p.5", "Time Created": null, "Time Published": "2017-04-10T14:59:29Z", "Duration": null, "Description": "In this Python plays Grand Theft Auto tutorial, we're going to incorporate the Hough Line finding functionality from OpenCV.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BkyMzqomsNY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Bodyweight-Only Bedroom Workout (follow along)", "Time Created": null, "Time Published": "2020-03-17T03:58:04Z", "Duration": null, "Description": "This 10-minute bodyweight-only workout can be performed anywhere, including your bedroom. Remember, the goal isn't to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hsQ9efb6a7c", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "6 Techniques That Help Me Study Machine Learning Five Days Per Week", "Time Created": null, "Time Published": "2021-09-26T02:41:28Z", "Duration": null, "Description": "In 2017, I started my own AI Master's Degree to learn machine learning by combining different resources. Studying online and on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IMMDPzECrf0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "5 Beginner Friendly Steps to Learn Machine Learning", "Time Created": null, "Time Published": "2019-09-15T12:00:59Z", "Duration": null, "Description": "This video breaks down practical steps on how to learning machine learning with Python. It's the video I wish I had watched when I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WJ18JZKvt6s", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "ResNets are back baby!!! ...and they're gone | Machine Learning Monthly March 2021", "Time Created": null, "Time Published": "2021-04-03T06:45:33Z", "Duration": null, "Description": "Machine Learning Monthly covers the latest and greatest (but not always the latest) in machine learning of the previous month.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7R08MPXxiFQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "These books will help you learn machine learning", "Time Created": null, "Time Published": "2019-08-18T10:04:03Z", "Duration": null, "Description": "Machine learning engineer Daniel Bourke shares some of the best books for learning machine learning. I've been learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_1CaUOHhI6U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Setup Apple Silicon Mac for Machine Learning in 13 minutes (TensorFlow edition)", "Time Created": null, "Time Published": "2021-12-05T11:00:18Z", "Duration": null, "Description": "How to get your Apple M1, M1 Pro, M1 Max or M1 Ultra Mac setup for data science and machine learning. In this video, we install ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ya5NwvKafDk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I passed the TensorFlow Developer Certification exam (and how you can too)", "Time Created": null, "Time Published": "2020-06-10T02:06:17Z", "Duration": null, "Description": "At the start of May, I decided to take the TensorFlow Developer Certification. So I created myself a curriculum to sharpen my ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Zx2MHdRgAIc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Setup Apple Silicon Mac for Machine Learning in 11 minutes (PyTorch edition)", "Time Created": null, "Time Published": "2022-05-22T11:41:13Z", "Duration": null, "Description": "Setup your Apple M1, M1 Pro, M1 Max or M1 Ultra Mac for data science and machine learning with PyTorch. Get the code on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cGvWz6Zv2nM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learning Data Science with My Brother! | Learning Intelligence 37", "Time Created": null, "Time Published": "2018-07-24T12:11:51Z", "Duration": null, "Description": "My brother and I started an applied data science course on Coursera. Links: Applied Data Science with Python ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MD3R9yatou0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Self-Studying Machine Learning? Remind yourself of these 6 things", "Time Created": null, "Time Published": "2019-03-02T22:23:30Z", "Duration": null, "Description": "Machine learning engineer Daniel Bourke shares his tips for self-studying machine learning. Leanring machine learning can be ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-pvFvVyrwJg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "A simple study break meal for optimizing mental performance", "Time Created": null, "Time Published": "2019-10-19T11:55:57Z", "Duration": null, "Description": "Food is the force multiplier of life, if you do it right, cooking and eating healthy can help with focus, mental performance and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TZr21df2plE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity AI Nanodgree - Learning how to build a SMART SPEAKER | Learning Intelligence 31", "Time Created": null, "Time Published": "2018-05-12T17:00:05Z", "Duration": null, "Description": "I started the final project of the Udacity Artificial Intelligence Nanodegree. For this project, we're using end-to-end Deep Learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bedzsHNSKnA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I got Google Cloud Professional Data Engineer Certified", "Time Created": null, "Time Published": "2019-04-27T12:20:52Z", "Duration": null, "Description": "I've been upskilling myself on engineering data services on Google Cloud. I didn't meet the prerequisites for the Google Cloud ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JWYsWhR3Pxg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Apple's M1 Pro and M1 Max are faster than Google Colab (machine learning speed test)", "Time Created": null, "Time Published": "2021-12-05T11:15:12Z", "Duration": null, "Description": "Let's see how Apple's new M1 Pro and M1 Max deal with various machine learning workloads. Blog post with results ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GYRz3RAu4Bk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to learn data science with Coursera in 2022 (beginner-friendly)", "Time Created": null, "Time Published": "2022-01-08T06:29:23Z", "Duration": null, "Description": "This video details how to create your own beginner-friendly curriculum using Notion to learn Python, data science and machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PHUbdnviN7o", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Six Health Habits for Losing Weight and Keeping it Off", "Time Created": null, "Time Published": "2019-01-28T11:01:12Z", "Duration": null, "Description": "These health habits helped me lose weight and keep it off for the past 8-years. If you want to lose weight and keep it off, there's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lal7kgZH-0k", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The most important article on programming you\u2019ll ever read", "Time Created": null, "Time Published": "2021-12-12T10:00:21Z", "Duration": null, "Description": "If something's worth learning, enjoy it. Forget the rush. Learn slower. Teach yourself programming in 10 years ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yQvUU2YPPy4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to get experience as a beginner data scientist", "Time Created": null, "Time Published": "2020-07-05T06:57:22Z", "Duration": null, "Description": "Manuela emailed the other day asking \"how can a beginner data scientist like me get experience?\". The question followed up with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8gEa0nM-RGg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What I do when I don't feel like studying | Learning Intelligence 33", "Time Created": null, "Time Published": "2018-06-21T12:49:13Z", "Duration": null, "Description": "When I lack the motivation to study, I ask myself, \"what's the alternative?\" and use my answer as motivation. My AI Masters Degree ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cZ2HCclgQ-g", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I'd start learning machine learning again (3 years in)", "Time Created": null, "Time Published": "2020-09-13T02:30:12Z", "Duration": null, "Description": "Three years ago I started studying machine learning online in my bedroom. Two things are for sure: 1. I know a lot more than ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Nutpusq_AFw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The Unofficial PyTorch Optimization Loop Song", "Time Created": null, "Time Published": "2022-03-05T22:59:07Z", "Duration": null, "Description": "A fun song to help you remember how to write a training loop and a testing loop in PyTorch. The jingle is not endorsed by PyTorch ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mWbuVlIX5jg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Bioinformatics: Where code meets biology", "Time Created": null, "Time Published": "2019-02-15T11:35:33Z", "Duration": null, "Description": "I went through the start of the bioinformatics specialisation on Coursera. Bioinformatics is fascinating to me because it involves the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-Tz_fqHqva0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "800 Calorie Pancake of Peace | High Protein Pancake", "Time Created": null, "Time Published": "2017-04-26T10:31:03Z", "Duration": null, "Description": "I've cooked this breakfast food since 2013. It's taken me a few years but I think I've nailed the recipe and cooking method. Simple ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "smlQbh6jQvg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I got my machine learning model deployed! | Airbnb Amenity Detection Part 8", "Time Created": null, "Time Published": "2020-04-16T13:00:27Z", "Duration": null, "Description": "After a few days of fiddling around, I managed to get my amenity detecting machine learning deployed. I built an app around it ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OVk4QZ-la1Q", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Machine Learning INTERNSHIP Day 1 Takeaways | Learning Intelligence 29", "Time Created": null, "Time Published": "2018-04-21T04:14:43Z", "Duration": null, "Description": "Last week, I told you I got offered a data science/artificial intelligence internship. Here are the three things I think are most ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cCMENSO9cn4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "AI Meets Blockchain! | Learning Intelligence 5", "Time Created": null, "Time Published": "2017-10-12T02:22:36Z", "Duration": null, "Description": "Episode 5 of the Learning Intelligence series! Other than completing my second project of the Udacity AI Nanodegree, something ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hTHXVfryZDo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Using Machine Learning to Replicate Airbnb's Amenity Detection Part 2: Data Exploration", "Time Created": null, "Time Published": "2020-02-23T22:00:11Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2DUxjcVtcdI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The Ultimate Skill: Learning How to Learn (course review)", "Time Created": null, "Time Published": "2019-02-03T13:28:03Z", "Duration": null, "Description": "An in-depth review of the Learning How to Learn Course on Coursera. Learning How to Learn on Coursera ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pHiMN_gy9mk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "2020 Machine Learning Roadmap (95% valid for 2022)", "Time Created": null, "Time Published": "2020-07-12T15:00:12Z", "Duration": null, "Description": "Getting into machine learning is quite the adventure. And as any adventurer knows, sometimes it can be helpful to have a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vKHJrTHB5rM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "A balance you need to fix: Creation vs. Consumption", "Time Created": null, "Time Published": "2020-05-09T13:00:32Z", "Duration": null, "Description": "Imagine a world where instead of people doubling down on consuming, they doubled down on creating. That's a world I'd like to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a-IYqSw5ISs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "i left my machine learning job", "Time Created": null, "Time Published": "2019-06-26T03:49:03Z", "Duration": null, "Description": "14 months ago, I started as a machine learning intern at Max Kelsen. Then that internship rolled into a job as a machine learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "btLxTTkSZuY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The Hundred-Page Machine Learning Book Book Review", "Time Created": null, "Time Published": "2019-07-18T12:52:33Z", "Duration": null, "Description": "The Hundred-Page Machine Learning Book. The start here and continue here of machine learning. The book I wish I had when I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tpCFfeUEGs8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 1/2", "Time Created": null, "Time Published": "2021-03-16T10:21:23Z", "Duration": null, "Description": "Ready to learn the fundamentals of TensorFlow and deep learning with Python? Well, you've come to the right place. After this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PnuHj5bi-rg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My first day as a MACHINE LEARNING Engineer | Learning Intelligence 32", "Time Created": null, "Time Published": "2018-05-31T11:02:47Z", "Duration": null, "Description": "After a couple of weeks at the internship, I was offered a paid Machine Learning Engineer role! My AI Masters Degree ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Pp_OTo4SDD0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How the World's Biggest Companies Design Machine Learning Applications | ML Monthly April 2021", "Time Created": null, "Time Published": "2021-05-08T05:37:22Z", "Duration": null, "Description": "In this edition of Machine Learning Monthly, we take a look at how the world's biggest companies design machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8xxMWpl6giQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "This graph tells you whether you're intelligent or stupid", "Time Created": null, "Time Published": "2020-01-12T05:30:00Z", "Duration": null, "Description": "I recently read The Basic Laws of Human Stupidity by Carlo Cipolla and it's changed how I'm thinking about the new year. There's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CLxB7VxAr-E", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Bedroom Floor Mobility Session for Beginners (follow along)", "Time Created": null, "Time Published": "2020-03-26T09:09:41Z", "Duration": null, "Description": "This 10-minute bodyweight mobility session helps to alleviate the squeeze and tightness you usually get from sitting too long or ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ICMtmjRg0-Y", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "In-depth deeplearning.ai Specialization Review", "Time Created": null, "Time Published": "2018-07-28T09:05:49Z", "Duration": null, "Description": "The deeplearning.ai specialization is easily one of the best courses I've ever taken. I hope you get as much out of it as I did.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8JTKX09LzNc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Are courses enough for a job? | Machine learning engineer livestream Q&A", "Time Created": null, "Time Published": "2020-08-06T00:29:48Z", "Duration": null, "Description": "Let's talk machine learning, health, business and more. Timestamps: 0:00 - Intro 2:09 - No more mullet 4:40 - QA Start 4:50 - Is AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8zQZoknhBzw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I became a productivity machine", "Time Created": null, "Time Published": "2019-10-06T12:21:49Z", "Duration": null, "Description": "This video goes through some tips I use to manage my time more productively. Sid asked me the other day how I manage to get ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Z_ikDlimN6A", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learn PyTorch for deep learning in a day. Literally.", "Time Created": null, "Time Published": "2022-07-24T02:17:09Z", "Duration": null, "Description": "Welcome to the most beginner-friendly place on the internet to learn PyTorch for deep learning. All code on GitHub ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oqnq8miWVq0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Apple's New M1 Chip is a Machine Learning Beast (M1 vs Intel MacBook speed test)", "Time Created": null, "Time Published": "2020-12-24T11:00:14Z", "Duration": null, "Description": "At the start of the year I bought a nearly top spec Intel-based 16-inch MacBook Pro to edit videos and write code. Then Apple ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "UAsCJStV6Fg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I got offered a Machine Learning Engineer INTERNSHIP! | Learning Intelligence 27", "Time Created": null, "Time Published": "2018-04-11T11:33:38Z", "Duration": null, "Description": "After meeting up with someone my friend Mike introduced me to, I was offered a machine learning engineer internship at a tech ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZeCReYxxDFQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What does a head of data science look for in a junior? | Interview with Ken Jee", "Time Created": null, "Time Published": "2020-07-16T03:15:13Z", "Duration": null, "Description": "Ken Jee is the head of data science at Scouts Consulting, a data science team which helps sports teams and athletes improve ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f1y9wDDxWnA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Code with me (live): How to make your first Kaggle submission from scratch!", "Time Created": null, "Time Published": "2018-12-02T05:03:43Z", "Duration": null, "Description": "Let's explore the Kaggle Titanic data and make a submission together! Thank you to Coursera for sponsoring this video. You can ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "r2imindSw14", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to Create Your Own Data Science Curriculum with Coursera in 2021", "Time Created": null, "Time Published": "2021-01-04T12:11:53Z", "Duration": null, "Description": "If you're looking to learn data science in 2021, perhaps you might be interested in creating your own self-guided, self-paced ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AzSSTUJRlJo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "This book will help you get a job in machine learning (ML Interviews Book) | ML Monthly June 2021", "Time Created": null, "Time Published": "2021-07-03T05:59:35Z", "Duration": null, "Description": "Machine learning monthly covers the latest and greatest (but not always the latest) of the machine learning field from the previous ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0YUxK6g3U2M", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Training and Eating like a SPARTAN! Spartan Race Preparation", "Time Created": null, "Time Published": "2018-03-28T09:32:03Z", "Duration": null, "Description": "Zenith, Chris and I signed up for the upcoming Spartan Ultra in Brisbane on April 28 2018. The Spartan Ultra is an elite variation of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fw6NMQrYc6w", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to Deploy a Machine Learning Model to Google Cloud for 20% Software Engineers (CS329s tutorial)", "Time Created": null, "Time Published": "2021-02-14T06:21:38Z", "Duration": null, "Description": "It's time to reveal the magician's secrets behind deploying machine learning models! In this tutorial, I go through an example ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Etjp9VRYggE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "In-Depth Udacity Deep Learning Nanodegree Review", "Time Created": null, "Time Published": "2018-01-20T07:11:15Z", "Duration": null, "Description": "Welcome to my in-depth Deep Learning Nanodegree review video! I finished the Deep Learning Nanodegree in August of 2017.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nGnAGtMk-FM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Finishing the Udacity Artificial Intelligence NANODEGREE | Learning Intelligence 34", "Time Created": null, "Time Published": "2018-06-24T09:35:44Z", "Duration": null, "Description": "I submitted and passed the final project for the Udacity Artificial Intelligence Nanodegree. Send me a message on Telegram if ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DJQlxf7SFhg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Lunch at LinkedIn New York City (Empire State Building offices)", "Time Created": null, "Time Published": "2018-12-07T23:08:48Z", "Duration": null, "Description": "Big Easy (my Godfather Damien) and I (Little Easy) went to the LinkedIn New York City offices for lunch. The offices are in the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lgckzdv46kg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Bourke Brothers hit the library | Learning Intelligence 41", "Time Created": null, "Time Published": "2018-08-14T22:30:55Z", "Duration": null, "Description": "We hit the library to study. Will is working on an introduction to Python course, I'm working on an applied data science with Python ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wm5QkbQ5LFI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Morning Wake Up Stretching Routine for Beginners", "Time Created": null, "Time Published": "2020-03-30T08:47:10Z", "Duration": null, "Description": "This simple morning stretching routine will get your body and mind ready to take on the day. Do yourself a favour and spend ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cyLWtMSry58", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Don't learn machine learning", "Time Created": null, "Time Published": "2020-03-30T04:23:56Z", "Duration": null, "Description": "Should you learn machine learning? Yes, you should. But how? By avoiding being a donkey. There is an abundance of machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tiL7Y0iJmSg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "We Finished Spartan ULTRA 2018", "Time Created": null, "Time Published": "2018-06-19T11:31:56Z", "Duration": null, "Description": "On April 28, 2018, our legs took us further than they ever have in one day. Chris, Zeno and I ran the Spartan Ultra. A 50km+, 60+ ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GYzXJgS_p-4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Training TWO Weeks Out From Spartan Race", "Time Created": null, "Time Published": "2018-04-15T08:49:38Z", "Duration": null, "Description": "Spartan Race (Ultra) is a 50km trek with 60+ obstacles through the Gold Coast hinterland. I'm currently two weeks out and training ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZUKz4125WNI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learn TensorFlow and Deep Learning fundamentals with Python (code-first introduction) Part 2/2", "Time Created": null, "Time Published": "2021-03-17T04:23:48Z", "Duration": null, "Description": "You've made it to part 2 of the longest code-first learn TensorFlow and deep learning fundamentals video series on YouTube!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HnDyGCI9h2M", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Y Combinator Startup School week 1 progress", "Time Created": null, "Time Published": "2019-08-08T10:14:03Z", "Duration": null, "Description": "I signed up to the 2019 edition of the Y Combinator Startup School. I've learned a lot already. The two main things being: 1.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "C_lIenSJb3c", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Using Machine Learning to Replicate Airbnb's Amenity Detection Part 1: Overview", "Time Created": null, "Time Published": "2020-02-22T02:27:37Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "szw_8DQeIn8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "These 5 "ZUU" movements burn fat and train your whole body", "Time Created": null, "Time Published": "2020-04-09T08:08:42Z", "Duration": null, "Description": "ZUU is a style of training taking over Australia and the rest of the world. I love it for its simplicity, animal-inspired bodyweight ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ooB-ZU9iLmI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I got Detectron2 working! | Airbnb Machine Learning Project Part 4", "Time Created": null, "Time Published": "2020-03-08T01:52:35Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0Vku4lRnkuQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My first week running an online business", "Time Created": null, "Time Published": "2019-07-07T09:37:37Z", "Duration": null, "Description": "Two weeks ago, I left my job as a machine learning engineer to go full-time on my own business. I make videos and write about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gxMOoNQEIjE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Starting Term 2 of the Udacity Artificial Intelligence Nanodegree | Learning Intelligence 19", "Time Created": null, "Time Published": "2018-02-04T18:30:01Z", "Duration": null, "Description": "Welcome to the nineteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pmCnEJ7Wl5U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The Applied Data Science Course is epic! | Learning Intelligence 42", "Time Created": null, "Time Published": "2018-08-18T01:10:35Z", "Duration": null, "Description": "The Applied Data Science with Python Specialization on Coursera is turning out to be one of the best I've ever done. I'd highly ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jIiBaYvsM60", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "These TensorFlow updates are huuuuuuuuge! [Google I/O 2021] | Machine Learning Monthly May 2021", "Time Created": null, "Time Published": "2021-06-07T11:20:20Z", "Duration": null, "Description": "Machine learning monthly covers the latest and greatest (but not always the latest) of the machine learning field from the previous ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2eK3jDkLeCU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I've got a new favourite machine learning book | Machine Learning Monthly October 2020", "Time Created": null, "Time Published": "2020-11-14T12:47:43Z", "Duration": null, "Description": "Every month I collect the most outstanding resources in the world of machine learning and put them together in a short report ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ubj5OyU-7GM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "COFFEE, YOGA and AWS | 100 Days of Code 5", "Time Created": null, "Time Published": "2017-06-02T08:31:59Z", "Duration": null, "Description": "It's been an epic couple of days! I managed to get a complete backend server running on a LEMP stack using AWS. That was a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bvBOzlDbrR8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity AI Nanodegree Project 4 Planning and Progress | Learning Intelligence 12", "Time Created": null, "Time Published": "2017-12-02T06:12:44Z", "Duration": null, "Description": "Welcome to the twelfth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "nZxKKCD0O-I", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I didn't eat food for 4 days, here's what happened", "Time Created": null, "Time Published": "2019-09-15T12:06:12Z", "Duration": null, "Description": "Last month, I did my first extended fast. I'd heard all of the benefits of fasting but hadn't tried anything longer than 24-hours before.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DBbBRwpneLs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Data scientists should be more end-to-end | Machine Learning Monthly September 2020", "Time Created": null, "Time Published": "2020-10-10T13:50:35Z", "Duration": null, "Description": "Every month I review the latest and greatest resources in the world of machine learning in a newsletter called Machine Learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sd5VndgniHI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Finishing fast.ai Deep Learning Course Part 1 | Learning Intelligence 35", "Time Created": null, "Time Published": "2018-07-19T12:26:33Z", "Duration": null, "Description": "I finished the first part of the fast.ai deep learning course and it's fast (get it?) becoming one of my favourite courses. Links from the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "W5XNOmyJr6I", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building a machine learning app | 10 hour coding livestream", "Time Created": null, "Time Published": "2021-11-06T09:03:23Z", "Duration": null, "Description": "Time to celebrate 100k subscribers! And what better way to do it than with a coding livestream? Tune in for 10 hours straight (give ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rZ5WbQZpQa0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I didn't eat food for 5 days, here's what happened", "Time Created": null, "Time Published": "2020-10-19T11:12:52Z", "Duration": null, "Description": "A couple of weeks ago, I completed my first ever five day fast. This video shares what happened. The video is split into two parts: 1 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qjUeeWvlBgE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Using Stack Overflow to Learn From the Best | Learning Intelligence 40", "Time Created": null, "Time Published": "2018-08-09T06:12:01Z", "Duration": null, "Description": "I made some progress on the Applied Data Science with Python Specialization on Coursera. It's turning out to be a really valuable ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "btjp5PE96Sw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Passed the Final Data Science Assignment! | Learning Intelligence 46", "Time Created": null, "Time Published": "2018-11-11T12:36:11Z", "Duration": null, "Description": "Woohoo! I passed one of the hardest assignments I've done yet, the final project for the Introduction to Data Science with Python ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HtSeYhm1e7A", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Lower Body Bodyweight Workout for Beginners", "Time Created": null, "Time Published": "2020-04-03T07:09:41Z", "Duration": null, "Description": "It's Friday and you know what that means, leg day baby. Follow along with this 10-minute lower body workout you can do ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "P-J0UdR6UUg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Want ripped arms? Buy yourself a pair of gymnastic rings | 30-minute whole body park workout", "Time Created": null, "Time Published": "2020-02-29T03:10:52Z", "Duration": null, "Description": "If I had to pick the top 2 pieces of equipment to workout with, gymnastic rings and kettlebells would be tied. This park workout uses ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Eaj7pNeIQhs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "A Day In The Life Of A Machine Learning Engineer | Learning Intelligence 36", "Time Created": null, "Time Published": "2018-07-21T14:32:52Z", "Duration": null, "Description": "A day in the life of what it's like to be a machine learning engineer. LINKS FROM THE SHOW: My AI Masters Degree ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "U6tKyaDdwNs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Burn fat and have fun with these unconventional movements *follow along*", "Time Created": null, "Time Published": "2020-04-12T09:33:55Z", "Duration": null, "Description": "Movement should be anything but conventional. When you first try these movements, they might feel strange compared to what ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2L85UZVJJbo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Coursera Deep Learning Specialization Progress | Learning Intelligence 15", "Time Created": null, "Time Published": "2017-12-26T23:20:38Z", "Duration": null, "Description": "Welcome to the fifteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pf16jm3Iiqg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Inside a $600,000,000 Australian Tech Company", "Time Created": null, "Time Published": "2018-06-30T01:53:09Z", "Duration": null, "Description": "I went on a little tour of the REA Group offices in Melbourne, Australia. I talked to people from all over the business and recorded a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "C7rp4oNKGfs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Applied Data Science with Python on Coursera Progress | Learning Intelligence 45", "Time Created": null, "Time Published": "2018-11-04T13:42:13Z", "Duration": null, "Description": "Special thanks to Coursera for offering to sponsor this video. I love joining forces with epic people and Coursera has a whole team ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7zVQSzbAhQU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The 100 Days is Over! | 100 Days of Code 17", "Time Created": null, "Time Published": "2017-08-26T11:01:36Z", "Duration": null, "Description": "What a journey it has been! Here's to the next 1000 days. Links mentioned in the video: Medium 100 Days of Code Series ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "5yF1KvAORaU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Using genetic algorithms to manipulate DNA (experiment)", "Time Created": null, "Time Published": "2019-03-30T06:52:27Z", "Duration": null, "Description": "I've been going through the Coursera Bioinformatics Specialization learning how to manipulate DNA nucleotide strings with code.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3p7-yQmo7A8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Taking Bumblebee for a drive! (455hp Camaro SS)", "Time Created": null, "Time Published": "2018-10-22T11:00:20Z", "Duration": null, "Description": "I'm not a big fan of driving along the American West Coast was pretty damn cool. Officially the fastest car I've ever been in.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4zPc0Q63Tv0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "AI makes you an artist + Tesla's self-driving car updates | Machine Learning Monthly August 2021", "Time Created": null, "Time Published": "2021-09-07T04:31:06Z", "Duration": null, "Description": "Machine learning monthly covers the latest and greatest (but not always the latest) of the machine learning field. Every month, get ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f5ZyqIueWPc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Graduating From the Udacity Deep Learning Nanodegree | 100 Days of Code 15", "Time Created": null, "Time Published": "2017-08-13T02:03:34Z", "Duration": null, "Description": "This week I graduated from the Deep Learning Nanodegree Foundations from Udacity. Before I even started, I emailed the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "L8Sd1rRGcOw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to make your first pull request (and how I made mine)", "Time Created": null, "Time Published": "2019-06-06T07:54:13Z", "Duration": null, "Description": "I made my first contribution to an open source library by making a pull request to the fastai deep learning repository! Not sure what ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "99h6CLLUVog", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Drawing Flowers in Python", "Time Created": null, "Time Published": "2017-03-25T02:05:18Z", "Duration": null, "Description": "Disclaimer: I'm only a beginner programmer so what I say in the video should not be taken as gospel. I'm just uploading what I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Vn7JL1gQaLs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Full Body Workout Using 2 Chairs", "Time Created": null, "Time Published": "2020-04-01T09:49:53Z", "Duration": null, "Description": "Grab 2 chairs and join in for this full-body, bodyweight-only workout. This video was recorded during the COVID-19 lockdowns.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "p0cOW2cd458", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "30-minute Full Body Prison Style Workout *follow along, no equipment needed*", "Time Created": null, "Time Published": "2020-04-15T10:03:05Z", "Duration": null, "Description": "This full-body bodyweight-only workout isn't for the faint of heart. Find some space on your floor and get ready to sweat. Day 30 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "VLQHpvuwsV0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Graduating from the deeplearning.ai Coursera Specialization | Learning Intelligence 22", "Time Created": null, "Time Published": "2018-02-24T17:30:00Z", "Duration": null, "Description": "I finished the Coursera deeplearning.ai specialization by Andrew Ng! Coursera for Deep Learning Specialisation ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9W7IA0_D1qw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Upgrade your decision making using these 4 boxes", "Time Created": null, "Time Published": "2020-05-16T13:00:05Z", "Duration": null, "Description": "What's important or non-important? What's urgent and non-urgent? When do these crossover? Best not to get them confused.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "273TgoQB_yQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Bodyweight Only Core Workout for Beginners to Advanced", "Time Created": null, "Time Published": "2020-04-04T09:04:17Z", "Duration": null, "Description": "If you're looking to build your core strength at home, all you need is your body weight and gravity. This was recording during the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Iw2yN9RXyJY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to code neural networks without math*", "Time Created": null, "Time Published": "2021-10-17T07:22:24Z", "Duration": null, "Description": "When I code neural networks, I think about them write them in layers, often not thinking about the math that runs behind the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2l5puQ-KYb0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Replicating Airbnb's Machine Learning Powered Amenity Detection Project | Code Walkthrough (live)", "Time Created": null, "Time Published": "2020-03-11T07:04:10Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oq08FVD44CA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Staying Fit While Travelling | San Francisco Hostel Workout", "Time Created": null, "Time Published": "2018-10-28T01:27:36Z", "Duration": null, "Description": "Just because you're on tour doesn't mean the gains don't stop! Biology is a 24/7 process. Keep moving. I did this little circuit in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cijajMJ3m3w", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Replicating Airbnb's Machine Learning Powered Amenity Detection Part 3: Data Manipulation", "Time Created": null, "Time Published": "2020-03-01T02:58:47Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "S6u6kO1GGXc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Completing Andrew Ng's Machine Learning Course on Coursera | 100 Days of Code 12", "Time Created": null, "Time Published": "2017-07-23T04:55:01Z", "Duration": null, "Description": "Last week, I finished the Machine Learning course from Standford University and Andrew Ng on Coursera. I also learned more ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1lyVMSQzIwc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Completing Google Cloud Platform Machine Learning Fundamentals | Learning Intelligence 44", "Time Created": null, "Time Published": "2018-09-13T23:26:53Z", "Duration": null, "Description": "We've started working on becoming Google Cloud certified at Max Kelsen. I'm on the data engineering track and just completed ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Wvl1ajhJs8c", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Passed the NLP CAPSTONE of the Udacity AI Nanodegree! | Learning Intelligence 26", "Time Created": null, "Time Published": "2018-04-01T05:22:59Z", "Duration": null, "Description": "I passed the final natural language processing project of the Udacity Artificial Intelligence Nanodegree. In the NLP capstone I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "lH6lU-DcBBc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to deal with imposter syndrome", "Time Created": null, "Time Published": "2019-11-16T08:43:33Z", "Duration": null, "Description": "Imposter syndrome happens when the narrative you tell yourself doesn't match up with the one you're living out. It never goes ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fPDy_qY1v1o", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learning Programming? You should try Anki | Learning Intelligence 38", "Time Created": null, "Time Published": "2018-07-31T11:46:46Z", "Duration": null, "Description": "Anki is one of my favourite tools for helping me to learn new things like a boss. It's free, give it a try! LINKS FROM THE SHOW: My ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "S8Tjnr9hkKE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Broomstick Fitness - 10-minute full body bodyweight workout with a broomstick", "Time Created": null, "Time Published": "2020-03-24T08:47:23Z", "Duration": null, "Description": "Aside from cleaning the house, the broomstick in your cupboard can also be used for a whole-body bodyweight workout.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-EGrINyWuss", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Finishing the Treehouse Python Track | 100 Days of Code 13", "Time Created": null, "Time Published": "2017-07-30T10:47:28Z", "Duration": null, "Description": "This week I finished the Treehouse Learn Python Track! I also started learning about semi-supervised learning with GANs.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "0hTrUQ_Mrn4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "BJJ White Belt Competition - How I won my first competition (with commentary)", "Time Created": null, "Time Published": "2019-10-27T11:26:12Z", "Duration": null, "Description": "A year ago, I entered my first BJJ competition as a white belt. Two weeks ago another BJJ competition and after 11 fights, I won ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jvB2DpIN_u4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Text/Profanity Checker in Python", "Time Created": null, "Time Published": "2017-03-25T02:05:17Z", "Duration": null, "Description": "Disclaimer: I'm only a beginner programming so what I say in the video should be taken as gospel. I'm just uploading what I learn.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JttLhotOrZw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Data Engineering on Google Cloud Platform Specialization Progress | Learning Intelligence 47", "Time Created": null, "Time Published": "2018-11-18T13:03:23Z", "Duration": null, "Description": "I've been getting Google Cloud Platform Certified on Coursera lately. Except I hit a bit of roadblock...But we'll get that fixed and be ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4v7YFV8bAJo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What I do when I get STUCK on programming problems | Learning Intelligence 24", "Time Created": null, "Time Published": "2018-03-15T17:51:51Z", "Duration": null, "Description": "I've been learning Python for about a year now but I still consider myself a novice. Whenever I get stuck on a programming ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qLg4ZQZsCbU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I signed up for Y Combinator's Startup School", "Time Created": null, "Time Published": "2019-07-28T11:42:41Z", "Duration": null, "Description": "I signed up for Y Combinators Startup School 2019 edition. It's a free 10-week program to help you learn what it takes to build a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_ciTldPd5ck", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Vegetarian Eating for Fitness", "Time Created": null, "Time Published": "2017-08-28T08:15:27Z", "Duration": null, "Description": "Vegetarian Eating for Fitness. I filmed everything I normally eat in a day as well as a few short clips from a park workout. Lately ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MmRrSVQRuF4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What a programmer\u2019s desk looks like on Sunday", "Time Created": null, "Time Published": "2022-06-12T03:39:39Z", "Duration": null, "Description": "", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Nz7xzUybpFM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building a Deep Learning PC", "Time Created": null, "Time Published": "2020-09-06T10:58:18Z", "Duration": null, "Description": "I've been thinking about building my own deep learning PC for a while. Then two days in a row I got shut off from using GPUs on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HVuL4Xn9mDk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Fix your tight hips and shoulders in 10-minutes (ball joint mobility session)", "Time Created": null, "Time Published": "2020-04-08T08:15:02Z", "Duration": null, "Description": "Tight shoulders? Tight hips? This 10-minute mobility session will take care of those rusty ball joints. Grab a broomstick and find a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ixk2R1MwXX8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My new TensorFlow for Deep Learning course is now on Udemy! #shorts", "Time Created": null, "Time Published": "2021-04-29T05:52:26Z", "Duration": null, "Description": "The new Zero to Mastery TensorFlow for Deep Learning course is now available on Udemy! Sign up here: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "px5lkNy7XhI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I didn't eat food for 3 days, here's what happened", "Time Created": null, "Time Published": "2021-08-12T08:38:12Z", "Duration": null, "Description": "I did a 3 day water-only fast (no food, no coffee, no tea), just water and salt. I filmed what I got up to and turned it into a mini ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "kd0fHSgQ9uU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Functional Friday | Backyard Workout", "Time Created": null, "Time Published": "2017-03-17T13:03:56Z", "Duration": null, "Description": "One of my good friends Jay texted me this morning asking if I wanted to workout in my backyard. It was hot but I was also keen to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "EDOaQLm29SU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What gear should you bring on Spartan Race? + Final Training Session", "Time Created": null, "Time Published": "2018-05-06T16:00:01Z", "Duration": null, "Description": "We picked up all of the food and nutrition we'll be bringing with us during the Spartan Ultra. I also shortened my last training ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MCQ_Nv-9LCQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Leg Day at World Gym Northlakes ft. Ben Jones Fitness", "Time Created": null, "Time Published": "2018-02-12T17:30:00Z", "Duration": null, "Description": "Ben and I checked out one of the biggest gyms in our home city. My training has been varied lately whilst trying to maintain a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XQMVtVHOEQw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "5 Animal Style Movements in 10-minutes (follow along)", "Time Created": null, "Time Published": "2020-03-23T02:51:12Z", "Duration": null, "Description": "Get outdoors and get back to nature with these animal style movements. Use these movements for a low impact full-body workout.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iJfylKGAeq4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity Artificial Intelligence Nanodegree NLP Concentration Progress | Learning Intelligence 23", "Time Created": null, "Time Published": "2018-03-03T17:30:02Z", "Duration": null, "Description": "The Natural Language Processing section of Term 2 of the Udacity Artificial Intelligence Nanodegree is officially underway!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MMeIkbYJv3o", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What Is An Expert Generalist?", "Time Created": null, "Time Published": "2017-06-13T10:02:34Z", "Duration": null, "Description": "TDBS Episode 99! Specialising in one thing for my whole life scares me (at least at this point and time, it may change). There's so ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YaPXHoOo9Pw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Short Term vs Long Term Satisfaction", "Time Created": null, "Time Published": "2017-06-22T09:44:05Z", "Duration": null, "Description": "I decided to try a new episode format! Five minutes of Fire Friday's Let's see how long I can keep this up. The topic of this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZnBwuxs09kg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Beginner Friendly 20-minute Whole Body Bodyweight Only Workout", "Time Created": null, "Time Published": "2020-04-05T11:06:07Z", "Duration": null, "Description": "Follow along for this whole body bodyweight-only workout you can do at home, in your bedroom, your living room, anywhere.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IfcjM2C89no", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "High Protein Vegan Snack  - Crunchy Spicy Chickpeas", "Time Created": null, "Time Published": "2016-09-07T04:51:40Z", "Duration": null, "Description": "A quick and easy recipe for Crunch Spicy Chickpeas. The recipe was sourced from the Fit Men Cook app. Fit Men Cook app ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mN8G9fWOKP0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "It's going to be a big (and fast) Summer of learning | Machine Learning Monthly August 2020", "Time Created": null, "Time Published": "2020-09-19T05:23:13Z", "Duration": null, "Description": "From new Nvidia GPUs to using machine learning to enrich colonoscopy data to a brand new tutorial series on MLOps, it's been a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "cNDA60YLVdQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Level up your software engineering skills as a data scientist | ML Monthly February 2021", "Time Created": null, "Time Published": "2021-03-08T07:55:03Z", "Duration": null, "Description": "How do you go from a data scientist or machine learning researcher to building full-stack applications? In this episode of Machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HHpu8kfGej0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Studying Data Science at the Library | Learning Intelligence 39", "Time Created": null, "Time Published": "2018-08-04T22:37:29Z", "Duration": null, "Description": "My brother and I have been going to the library lately to practice coding with each other. He's learning Swift for iOS app ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M08ULJFJf4w", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Rainy day on the farm (preparing garlic)", "Time Created": null, "Time Published": "2021-12-20T03:30:50Z", "Duration": null, "Description": "Brodie and I preparing garlic from a recent harvest for sale in the rain. Location - Loop Growers, Brisbane, Australia Website ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3IKWukTiBfc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The future will not be supervised... | Machine Learning Monthly July 2020", "Time Created": null, "Time Published": "2020-08-09T06:06:03Z", "Duration": null, "Description": "This month has been all about GPT3 and self-supervised learning. GPT3 is the latest in language modelling from OpenAI and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aBkUE5OJ8u8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What could be improved? Machine Learning Project Retrospective | Airbnb Amenity Detection Part 9", "Time Created": null, "Time Published": "2020-04-30T13:00:00Z", "Duration": null, "Description": "At the end of any project, it's essential to look back and ask two questions: What went well? and What could be improved? In this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "D1VbL8kn3rY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Try Going Over It Again | Learning Intelligence 3", "Time Created": null, "Time Published": "2017-09-27T11:15:49Z", "Duration": null, "Description": "Part 3 of my Learning Intelligence series! Previously, I'd had some trouble understanding some of the concepts in the Udacity AI ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tfrBuQl5iQI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "One Neural Network to Rule Them All (and more) | Machine Learning Monthly June 2020", "Time Created": null, "Time Published": "2020-07-06T10:30:06Z", "Duration": null, "Description": "Every month I write an article called Machine Learning Monthly which collects all the coolest things in machine learning I've found ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "65DJ0XRZLiQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Deep Learning\u2019s Most Important Ideas | Machine Learning Monthly November 2020", "Time Created": null, "Time Published": "2020-12-05T11:00:14Z", "Duration": null, "Description": "Every month I publish a newsletter called Machine Learning Monthly, which gathers the latest, greatest and most important things ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "A7f7uy4OLJA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Python and Pullups | Learning Intelligence 4", "Time Created": null, "Time Published": "2017-10-05T01:54:27Z", "Duration": null, "Description": "Welcome to video 4 of my Learning Intelligence series! If you've been following along, you know I love to exercise about as much ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HNdUCVE_3K0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I made my first $1500 online: The 2-Year Self Apprenticeship", "Time Created": null, "Time Published": "2020-01-25T08:42:08Z", "Duration": null, "Description": "Making money online is something I thought I could never do. Until I did. I made my first $1500 online at the end of 2018 (3 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fhNAQhsRyS4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Create something (Neue) every day ft. amazing chair review", "Time Created": null, "Time Published": "2020-01-30T11:45:27Z", "Duration": null, "Description": "I ordered a NeueChair the other day and it arrived today. I was so excited I had to put it together, try it out and review it straight ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "y0vr157clVc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Don't let perfect hold back progress | Learning Intelligence 49", "Time Created": null, "Time Published": "2018-12-28T06:30:00Z", "Duration": null, "Description": "I finished the Google Cloud Data Engineering Certification on Coursera! Now to get ACTUALLY certified. Try out the Google ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1nMOjy23MQc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building a business from a bedroom | Ask me anything! (live)", "Time Created": null, "Time Published": "2020-05-30T00:19:22Z", "Duration": null, "Description": "I've been building a business for the past year or so from my bedroom, teaching machine learning, making videos, writing.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mOWA_1r_NUA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Machine Learning Engineer reacts to State of AI Report 2019", "Time Created": null, "Time Published": "2019-08-11T11:42:43Z", "Duration": null, "Description": "Machine learning engineer, Daniel Bourke, reviews the State of AI Report 2019 edition. The State of AI reports covers some of the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "r4p40YTrLAc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Who said robots can't dance? | Machine Learning Monthly December 2020", "Time Created": null, "Time Published": "2021-01-17T08:24:42Z", "Duration": null, "Description": "Dancing robots, AlphaFold 2, MuZero, software engineering and AI, CS50 meets AI and more! As usual, another massive month in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "OtznK7I11s8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Is 13 too young to start learning machine learning? | 97,777 Subscriber Livestream Q&A", "Time Created": null, "Time Published": "2021-10-16T02:22:39Z", "Duration": null, "Description": "Come and celebrate 97777 subscribers with me and ask me anything. Why 97777? I like the number 7. Links: Learn ML ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eoLUlsBhjHo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My Self-Created Artificial Intelligence Master's Degree | Learning Intelligence 0", "Time Created": null, "Time Published": "2017-09-22T22:50:37Z", "Duration": null, "Description": "My Self-Created Artificial Intelligence Master's Degree | Learning Intelligence [0] Welcome to my Learning Intelligence series!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ypMXTie7qqQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Machine Learning INTERNSHIP Day 2 | Learning Intelligence 30", "Time Created": null, "Time Published": "2018-05-05T16:00:05Z", "Duration": null, "Description": "I'm learning so much at my Machine Learning Internship. Nothing beats hands-on experience. Leave a comment or message me ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dFoBt8xjtUc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My Experience at CodeCamp, Intro to Keras and Failing Hard | Learning Intelligence 17", "Time Created": null, "Time Published": "2018-01-14T11:48:29Z", "Duration": null, "Description": "Welcome to the seventeenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "giTul6io6-U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Predicted The Apple Watch In 2004", "Time Created": null, "Time Published": "2017-06-19T06:48:26Z", "Duration": null, "Description": "Day 85 of The Daniel Bourke Show 100-day experiment! I managed to find my first ever public speaking speech. I performed this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gKNLakS31Vw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Hand feeding goats at the farm", "Time Created": null, "Time Published": "2022-02-19T22:12:46Z", "Duration": null, "Description": "I've been going to a farm one day a week for the past couple of months. I'd like to own a large piece of land in the future. So I'm ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "w1g8-t0EXXY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I left my machine learning job - Ask Me Anything (live)", "Time Created": null, "Time Published": "2019-06-30T06:13:23Z", "Duration": null, "Description": "I recently left my machine learning job in Brisbane to go full-time on my own business. Ask me anything about why I left, what I'm ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "UUSxEdwbK_U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Data science hiring tips from a Senior Data Scientist | Inside REA Part 4", "Time Created": null, "Time Published": "2018-07-12T11:41:29Z", "Duration": null, "Description": "I sat down with the Chief Data Scientist and Chief UX Designer of REA Group and asked them what were the things they looked ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Md6UOfiBXFo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I screwed up | Inside a $600 Million tech company - Part 3", "Time Created": null, "Time Published": "2018-07-08T19:32:30Z", "Duration": null, "Description": "I went on the road with an REA sales executive and then sat down with a senior Data Scientist and UX Designer. Part 1: Exploring ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wgMpSHcOgzI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Ask a Machine Learning Engineer Anything (live) | March 2019", "Time Created": null, "Time Published": "2019-03-31T10:26:26Z", "Duration": null, "Description": "Ask machine learning engineer anything! I'm a 'self-taught' (I studied online) machine learning engineer who lives in Brisbane, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GExzDgDK6Vs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "It's my birthday! Come and ask me anything! (livestream party)", "Time Created": null, "Time Published": "2019-09-01T03:27:29Z", "Duration": null, "Description": "It's my 26th birthday! Let's have a livestream party! My favourite AI and ML resources - http://bit.ly/AIMLresources CONNECT: Web ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eiA3EEeGAZc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "34,835 training images downloaded | Replicating Airbnb's Amenity Detection Part 6", "Time Created": null, "Time Published": "2020-03-24T21:00:19Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CD4dmQ0iXUs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building a Deep Learning Image Classifier | Learning Intelligence 43", "Time Created": null, "Time Published": "2018-08-31T18:30:02Z", "Duration": null, "Description": "Josh and I have been thinking about using CoreML on the iPhone to harness the power of an image classifier machine learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dB3i3MvJH6U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "sending my first online business invoice ($$$) + new home gym", "Time Created": null, "Time Published": "2019-08-04T12:24:12Z", "Duration": null, "Description": "It's been a month since I left my job and went full-time on my own online business. This week I sent my first official invoice.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ToZyCA0uvoI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What Is Neuralink??! - TDBS 22 April 2017", "Time Created": null, "Time Published": "2017-04-23T11:37:29Z", "Duration": null, "Description": "Yesterday I spoke about Neuralink, a company Elon Musk is putting together. On his recent adventure to improve humanity, this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xBUdK9LakcA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What's the most challenging skill you needed to learn in your career? | 69,420 Subscribers Live Q&A", "Time Created": null, "Time Published": "2020-12-18T02:08:59Z", "Duration": null, "Description": "69420 subscribers!!! Let's do a live Q&A Bonus points if you get the reference... ;) Note: the audio drops between 31:54 and 35:20.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FPg0do4TPa0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building my first Amazon Alexa Skill! | Learning Intelligence 28", "Time Created": null, "Time Published": "2018-04-14T07:12:28Z", "Duration": null, "Description": "I'm into the voice user interfaces section of Udacity's Artificial Intelligence Nanodegree. One of the projects is to build your very ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JSjghKesig0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Ask a Machine Learning Engineer Anything (live) | April 2019", "Time Created": null, "Time Published": "2019-04-28T12:23:49Z", "Duration": null, "Description": "Ask Machine Learning Engineer Daniel Bourke anything. I'm a machine learning engineer based in Brisbane Australia and I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zkjcVD1YNV4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Travelling to the US", "Time Created": null, "Time Published": "2018-10-19T22:11:58Z", "Duration": null, "Description": "I went to the United States for a month taking only a backpack. And a couple weeks ago we gave a talk at my old university on AI.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JfwCT5SMjlA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Reading the first 42 pages of my first novel (Charlie Walks) out loud", "Time Created": null, "Time Published": "2021-09-01T01:54:40Z", "Duration": null, "Description": "Charlie Walks is the debut novel by Daniel Bourke, it tells the fictional story of a machine learning engineer who loves walks and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "L5Rgm_eoLyE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Ask a Machine Learning Engineer Anything (live) | May 2019", "Time Created": null, "Time Published": "2019-05-26T05:50:31Z", "Duration": null, "Description": "Ask machine learning engineer anything! Every month or so I host a livestream on my channel where I answer your questions live ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aQ-fPp5mvMU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Movement is medicine | 10-minute Bodyweight Bedroom Workout (follow along)", "Time Created": null, "Time Published": "2020-03-18T07:21:24Z", "Duration": null, "Description": "This 10-minute bodyweight workout can be performed anywhere, including your bedroom. Remember, the goal isn't to exhaust ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4rEe2Rhcwbk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Failed My First Two Years Of University - TDBS 21 April 2017", "Time Created": null, "Time Published": "2017-04-23T11:41:07Z", "Duration": null, "Description": "Perhaps the most important part of learning something new is enjoying what you're learning. It took me two years of failing ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "b5EhUcuncyY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "deeplearning.ai Progress! | Learning Intelligence 14", "Time Created": null, "Time Published": "2017-12-15T09:09:16Z", "Duration": null, "Description": "Welcome to the fourteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6uaFX8JQbww", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My second week running an online business", "Time Created": null, "Time Published": "2019-07-14T12:44:55Z", "Duration": null, "Description": "I'm into my second week running an online business. I want it to run for the long-term so the one metric I'm paying attention to and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "5PYhSkuLV1g", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Two things I'm doing wrong (running an online business)", "Time Created": null, "Time Published": "2019-07-21T09:27:38Z", "Duration": null, "Description": "My online business income currently comes through personalized professional projects for a range of clients. But in the past, I've ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pPgahuZyqLY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Running a business from a bedroom - Ask Me Anything (live)", "Time Created": null, "Time Published": "2019-08-02T01:35:55Z", "Duration": null, "Description": "Last month, I left my formal job as a machine learning engineer. Now I'm using those skills to run and build my own business.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ZMbcLuALc1A", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Got a chair? Try this 10-minute bodyweight only upper body workout", "Time Created": null, "Time Published": "2020-03-20T09:09:00Z", "Duration": null, "Description": "This 10-minute upper body bodyweight workout can be performed anywhere, including your bedroom, all you need is a chair.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ePShciy0Yto", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "2018: Thank you", "Time Created": null, "Time Published": "2018-12-31T04:00:01Z", "Duration": null, "Description": "2018 has been such an epic year. Thank you all for your support. Nothing motivates me more than seeing other people get after it ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eddlxBb543E", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Zero to Mastery Machine Learning Course Launch! | Ask me anything! (live)", "Time Created": null, "Time Published": "2020-01-19T00:21:39Z", "Duration": null, "Description": "One of my good friends Andrei Neagoie and I just launched a massive data science and machine learning course on Udemy!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YJ6xcSZfzRA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to go from tired to energized in 5-minutes (follow along workout)", "Time Created": null, "Time Published": "2020-04-14T10:12:43Z", "Duration": null, "Description": "Short on time? Short on energy? This 5-minute full-body session will leave you with more energy than you started. Beware: Don't ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "p5ZuhzUh81c", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Early Morning Animal Style Park Workout (bodyweight only)", "Time Created": null, "Time Published": "2020-03-14T00:01:01Z", "Duration": null, "Description": "Animal flow is one of the best styles of movement you can do because it can be done anywhere. You don't need any equipment, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Yi2oNZ7XuuI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How did I get a Machine Learning Engineer Role? - Livestream Q&A", "Time Created": null, "Time Published": "2018-06-02T02:27:39Z", "Duration": null, "Description": "Answering your questions from my latest video about getting a machine learning engineer role live on stream! My AI Master's ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "GpIguQwOsF8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Got 20-minutes? This whole body workout will help you get shredded", "Time Created": null, "Time Published": "2020-02-22T23:00:03Z", "Duration": null, "Description": "Justin, Sam and I have been doing some great home morning workouts in Justin's garage. We're focused on simple movements ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Uu_Qz-1uGSo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity Deep Learning Nanodegree Language Translation Project Submission | 100 Days of Code 10", "Time Created": null, "Time Published": "2017-07-07T00:47:39Z", "Duration": null, "Description": "My camera fell off a table and the lens was damaged (my fault) and now it doesn't open anymore. Rather than stop the VLOG ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SBLp0Z4pJko", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Bodyweight Back & Shoulders Bedroom Workout (follow along)", "Time Created": null, "Time Published": "2020-03-25T08:59:18Z", "Duration": null, "Description": "Back and shoulders are two of the harder muscle groups to train using only bodyweight movements. Not to worry, this 10-minute ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "94nGz6rLulk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "12-minute Upper Body Bodyweight Only Strength and Mobility Session", "Time Created": null, "Time Published": "2020-04-11T08:21:51Z", "Duration": null, "Description": "Build strength in your chest and mobility in shoulders with this 12-minute upper body bodyweight only session. This was recorded ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "JJXum5SA504", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity Artificial Intelligence Nanodegree Project 3 Progress | Learning Intelligence 8", "Time Created": null, "Time Published": "2017-11-03T08:27:10Z", "Duration": null, "Description": "Welcome to the eighth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4Uo5CPgF7Wg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Coronavirus Self-Isolation 10-minute Lower Body Bodyweight Workout (follow along)", "Time Created": null, "Time Published": "2020-03-21T08:47:12Z", "Duration": null, "Description": "This 10-minute lower body bodyweight workout can be performed anywhere, including your bedroom whilst on self-isolation.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wlLydjaHSWc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "5 Handstand Progression Exercises You Should Be Doing", "Time Created": null, "Time Published": "2017-11-21T10:57:33Z", "Duration": null, "Description": "If you're like me, your lack of upper body mobility and stability holds you back from being able to hold a handstand for longer than ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6RXASdkcnJs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Physique Update and 6 Things I Wish I Knew Before Starting Gym", "Time Created": null, "Time Published": "2017-08-19T23:46:46Z", "Duration": null, "Description": "A few weeks ago I answered a question on Quora which asked: \"What do I need to know before I go to the gym?\" I started thinking ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "v3UbklZAdbQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Training for Spartan Race is getting me JACKED!", "Time Created": null, "Time Published": "2018-04-07T23:15:21Z", "Duration": null, "Description": "Training for the Spatran Ultra Race has been brutal. But the results are showing, I'm putting on muscle and I'm the fittest I've ever ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Fe2DzBNIsMc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "You're Never Too Young to Start Learning AI - Learning Intelligence Talks with Shaik Asad", "Time Created": null, "Time Published": "2018-01-29T12:15:19Z", "Duration": null, "Description": "Recently, I had to privilege of talking with Shaik Asad is a 14-year-old AI developer from India. In the video, we go over how to start ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pxiPJ5aLiRI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What AI courses should you do? and What are my plans after finishing my studies? | Livestream Q&A", "Time Created": null, "Time Published": "2018-04-03T07:13:54Z", "Duration": null, "Description": "This was a bunch of fun! I'll definitely do more of these in the future. I was a little bit late but the stream was dedicated to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ynBw23pByFg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Data Science vs Data Processing vs Data Visualisation? | 3000 Subscriber Livestream", "Time Created": null, "Time Published": "2018-10-27T02:14:40Z", "Duration": null, "Description": "What's the deal between data science, data processing and data visualisation? Should you focus on one? Or learn them all?", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7GPfvSabCOA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Can you keep up? 10-minutes, 10 exercises *full body workout follow along*", "Time Created": null, "Time Published": "2020-04-07T07:33:14Z", "Duration": null, "Description": "This full-body home workout will have you breathing deep. 10 different exercises for 1-minute each with no rest. Being advised to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sVge7Ah68q8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How do I stay motivated? - 1000 Subscriber LIVE Q&A", "Time Created": null, "Time Published": "2018-04-22T05:16:16Z", "Duration": null, "Description": "To celebrate 1000 subscribers, I hosted a livestream where I answered frequent quesitons I get asked and anything else that ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YlZonIvipS8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Bedroom Floor 10-minute Upper Body Bodyweight Workout (intermediate)", "Time Created": null, "Time Published": "2020-04-02T09:58:39Z", "Duration": null, "Description": "This intermediate upper body bodyweight-only workout will get those delts pumped in no time. Staying home for Coronavirus ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NpX1gwOtA2w", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Computer Vision Basics + More deeplearning.ai Progress! | Learning Intelligence 16", "Time Created": null, "Time Published": "2018-01-07T12:17:24Z", "Duration": null, "Description": "Welcome to the sixteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SJqB4Jqea8Q", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learning about Generative Adversarial Networks on Udacity | 100 Days of Code 11", "Time Created": null, "Time Published": "2017-07-15T02:16:02Z", "Duration": null, "Description": "This week I started learning more about Generative Adversarial Networks. They've already blown me away. Links mentioned in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f9pztqE2QGM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Bayes Networks, Hidden Markov Models and How I Wake Up | Learning Intelligence 10", "Time Created": null, "Time Published": "2017-11-17T04:02:08Z", "Duration": null, "Description": "Welcome to the tenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YZNGTXZVakY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to Burn Over 100 Calories in 4 Minutes", "Time Created": null, "Time Published": "2017-08-31T12:52:30Z", "Duration": null, "Description": "How to Burn Over 100 Calories in 4 Minutes TABATA training is one of my favourite methods of cardio. It may be short but it's no ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qmPfQOU7aHU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to avoid knee surgery: Strengthen your glute medius (here's how)", "Time Created": null, "Time Published": "2020-04-13T09:45:30Z", "Duration": null, "Description": "This glute activating workout can be done as a warmup to a heavy hip hinge lift or as a stand-alone way to strengthen your glute ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "po6mCgWwlks", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "TWO WAYS TO INCREASE YOUR METABOLISM", "Time Created": null, "Time Published": "2017-08-05T23:59:57Z", "Duration": null, "Description": "Two of the only ways to really increase your metabolism. Say Hi to me anywhere! Web: www.mrdbourke.com Writing: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bqUD4ASNmIk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Biology and Physics meet Computer Science | Learning Intelligence 7", "Time Created": null, "Time Published": "2017-10-26T05:38:24Z", "Duration": null, "Description": "Welcome to the seventh instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MufZXpUdOyg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Mother's Day 2018", "Time Created": null, "Time Published": "2018-05-14T12:02:52Z", "Duration": null, "Description": "My brothers and I had no idea what to get our mum for Mother's Day, so we made her a video. We love you, mum! PS Make sure ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "H738L45p828", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "SLEEP YOUR WAY TO FAT LOSS", "Time Created": null, "Time Published": "2017-08-13T03:08:28Z", "Duration": null, "Description": "In this episode, I explore briefly how better sleep can lead to fat loss and 8 ways to sleep smarter. You may already be getting ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ukgXAOGGb3E", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "MY FIRST STARTUP WEEKEND | 100 Days of Code 6", "Time Created": null, "Time Published": "2017-06-06T00:09:30Z", "Duration": null, "Description": "This video includes days 22-25 of the 100 Days of Code series. I attended by first startup weekend! Though I did find out, what I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "h_9eAV5JGUk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity AI Nanodegree vs AI Masters Degree? | Livestream Q&A", "Time Created": null, "Time Published": "2018-07-14T00:54:25Z", "Duration": null, "Description": "I answer questions about Udacity Nanodegree's, what it's like being a machine learning engineer, what I'd do if I was back in high ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dKnOA45gEiY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What\u2019s the best kind of criticism? | Talking Thursday\u2019s with Josh", "Time Created": null, "Time Published": "2018-08-27T20:26:19Z", "Duration": null, "Description": "Josh and I sit down to talk about and answer questions from Quora. We answer things such as, \u201cWhat's the best form of criticism?", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2lHuddfEnHY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "TEACHING BOTS TO PLAY GAMES | 100 Days of Code 9", "Time Created": null, "Time Published": "2017-06-30T01:54:08Z", "Duration": null, "Description": "Over the past few days, I learned how Google's Deep Mind created AI bots that were able to learn how to play Atari games at a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "__p0ZfLkP40", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Full Day of Eating - Guessing My Macronutrient Ranges", "Time Created": null, "Time Published": "2017-04-19T21:38:21Z", "Duration": null, "Description": "I hadn't tracked anything I ate in over 6 months. I decided to see how accurate I was by just guessing the amount of food I would ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "2oMbUz5qiKc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Finishing Term 1 of Udacity's Artificial Intelligence Nanodegree | Learning Intelligence 13", "Time Created": null, "Time Published": "2017-12-08T07:24:24Z", "Duration": null, "Description": "Welcome to the thirteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "p6JDZaj8DxI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Facebook F8 Event Highlights, Amazon Shareholder Letters and Sleep with William Bourke", "Time Created": null, "Time Published": "2018-05-08T05:52:38Z", "Duration": null, "Description": "Listen on Anchor: https://anchor.fm/mrdbourke Or Apple Podcasts: http://bit.ly/bourkebrothers1 Connect with William ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "qFO1OvKvwDQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How I keep myself on track | 100 Days Of Code 8", "Time Created": null, "Time Published": "2017-06-21T11:36:38Z", "Duration": null, "Description": "I've always found I work better when my goals are laid out in front of me, nice and clear. So I created a yes and no list of the things ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hODZtpSCZZ0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "5 Simple Movements for Leg Strength and Mobility *follow along*", "Time Created": null, "Time Published": "2020-04-10T08:09:50Z", "Duration": null, "Description": "Mobility doesn't have to be divorced from strength. Improve your lower body mobility and leg strength with these bodyweight-only ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "w0_Zx7w4eDk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "GET-TO vs. HAVE-TO", "Time Created": null, "Time Published": "2017-08-15T11:30:58Z", "Duration": null, "Description": "Every morning I read a page of The Daily Stoic by Ryan Holiday and Stephen Hanselman. Each of the readings has some ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "83s-OEFMgVY", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Every model I build has to answer 1 simple question | Airbnb Machine Learning Project Part 5", "Time Created": null, "Time Published": "2020-03-10T03:30:49Z", "Duration": null, "Description": "I read an article the other which described how Airbnb uses computer vision and machine learning to automatically detect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sBpz_UUWFns", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Udacity AI Nanodegree Progress and Bayes' Rule Explained | Learning Intelligence 11", "Time Created": null, "Time Published": "2017-11-26T12:24:43Z", "Duration": null, "Description": "Welcome to the eleventh instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wFy-d3JLt_4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Submitting the Computer Vision Capstone Project | Udacity AI Nanodegree | Learning Intelligence 20", "Time Created": null, "Time Published": "2018-02-10T18:00:09Z", "Duration": null, "Description": "Welcome to the twentieth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "S1uXmq7HTns", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Simple 10-minute Bedroom Floor Bodyweight Core Workout for Beginners (follow along)", "Time Created": null, "Time Published": "2020-03-22T11:24:18Z", "Duration": null, "Description": "This 10-minute bodyweight only core workout can be performed anywhere, including your bedroom whilst in self-isolation.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "t2YbmnAFlRQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Functional Friday | Raw Training Australia", "Time Created": null, "Time Published": "2017-04-03T12:13:15Z", "Duration": null, "Description": "Joey and I went to our friend's gym. The focus was mobility and function. In a nutshell: 30 minutes of mobility work (stretching and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1kMNW4kwUhE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Being a Machine Learning Engineer - the Most Important Skills Needed | 2000 Subscriber Live Q&A!", "Time Created": null, "Time Published": "2018-08-26T10:14:20Z", "Duration": null, "Description": "I get asked a lot of questions and always do my best to answer them for everyone. Many of the questions and answers contain ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "E_PDMB6Rg8s", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "3 Benefits of Cold Showers", "Time Created": null, "Time Published": "2017-05-05T06:00:12Z", "Duration": null, "Description": "I've been taking cold showers for the past few months. At the start they sucked and they still suck but the feeling I get after taking ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "eTxeuWZY7tA", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "FALLING IS FUN | Functional Friday 4", "Time Created": null, "Time Published": "2017-05-05T06:30:15Z", "Duration": null, "Description": "Another session in the books at Raw Training Australia! This time we focused mainly on mobility. There was supposed to be some ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "80MnhMVWFhE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Xbox One S Unboxing and Xbox One Comparison", "Time Created": null, "Time Published": "2016-08-03T05:22:01Z", "Duration": null, "Description": "Unboxing the Xbox One S and comparing it to the original Xbox One on release day in Australia. This is my first video so feedback ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_ngpdGqnxSQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Finally Realised... - TDBS 16 April 2017", "Time Created": null, "Time Published": "2017-04-17T00:55:40Z", "Duration": null, "Description": "I decided to try out video recording the podcast. I want to start making more YouTube videos so I figured why not start with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MCmuRMZ4yLE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Finding The Right Medium - TDBS 18 April 2017", "Time Created": null, "Time Published": "2017-04-19T08:59:44Z", "Duration": null, "Description": "Over the past few weeks, I've been increasing the amount of media I've been putting out. This has been through podcasting, ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "hmT1xFCbZXU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Why your studying routine is f*cked", "Time Created": null, "Time Published": "2019-09-22T12:24:30Z", "Duration": null, "Description": "If you want your studying routine to continue being f*cked, do the opposite of what's in this video. After two years of studying alone ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tJ4cw-4t0V4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "TensorBoard and learning from Einstein | 100 Days of Code 3", "Time Created": null, "Time Published": "2017-05-24T23:20:13Z", "Duration": null, "Description": "Welcome to Episode 3 of the 100 Days of Code VLOG series! Doing 1 learning task per day has proved to be much better. Things ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Bm1gswXQAZs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Simple (but very difficult) Morning Home Workout", "Time Created": null, "Time Published": "2020-02-13T04:40:28Z", "Duration": null, "Description": "This simple yet effective morning home workout is helping Justin and I in the Brazilian Jiu-Jitsu arena, stay shredded and get ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oj1m0-37GIE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Self-Awareness Is A Super Power - TDBS 24 April 2017", "Time Created": null, "Time Published": "2017-04-26T10:01:46Z", "Duration": null, "Description": "I've been finding it hard lately to switch off. Especially when hanging out with friends, I consistently feel like I should be working.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-RUU7gaqn6s", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Attention, please", "Time Created": null, "Time Published": "2017-06-27T08:46:32Z", "Duration": null, "Description": "104 of The Daniel Bourke Show Another five minutes of fire! Skip ahead a few minutes if you want to miss the short intro. Recently ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "vzOsxC7upgc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I'm doing NaNoWriMo 2017!!!!!", "Time Created": null, "Time Published": "2017-10-31T12:05:58Z", "Duration": null, "Description": "What is NaNoWriMo? NaNoWriMo = National Novel Writing Month Aside from fitness, tech and food, writing is another of my loves ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_WdcQOXIU7A", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "NEW TensorFlow Deep Learning Course Release Celebration/QA", "Time Created": null, "Time Published": "2021-02-25T23:08:12Z", "Duration": null, "Description": "A few months ago I got TensorFlow Developer Certified. And a bunch of people asked how they could too. So I decided to make a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SIE3y4TfB3I", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "L-sit Progressions Workout", "Time Created": null, "Time Published": "2017-09-22T23:00:49Z", "Duration": null, "Description": "L-sit Progressions and Movement Workout This week at Raw Training Australia, Dave, Jay and I worked on our L-sit. The goal of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aO6DLMZ0sP4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Backyard Bodyweight & Callisthenics Workout | Live Recording", "Time Created": null, "Time Published": "2017-09-07T04:21:41Z", "Duration": null, "Description": "Backyard Bodyweight & Callisthenics Workout | Live Recording My first YouTube live video! This workout was recorded live from ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "KxVKeIZBqAE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The most valuable skill I've learned", "Time Created": null, "Time Published": "2017-06-12T07:11:04Z", "Duration": null, "Description": "The majority of problems I've faced in life have arisen from some kind of lack of communication. How can we communicate better ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3fcxA0JslPI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What I Learned From Creating My Own Radio Show - TDBS 101", "Time Created": null, "Time Published": "2017-05-25T06:35:41Z", "Duration": null, "Description": "We're back! I was never going to stop after 100 episodes. I'm going to try and keep this up as a weekly occurrence, watch this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "krH-YeHnoes", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Three Keys to a Good Warmup", "Time Created": null, "Time Published": "2017-09-30T06:52:00Z", "Duration": null, "Description": "Every good warmup should have these three things: 1. Stabilise the body, connect the mind and muscles 2. Activate the muscles ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "R1-dBaxCzNs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "WHAT I'VE LEARNED FROM TALKING TO PEOPLE", "Time Created": null, "Time Published": "2017-08-13T09:19:59Z", "Duration": null, "Description": "VIDEO UPDATE: I realised my head was cut off from the frame after recording the video, I will ensure this doesn't happen in the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TOpmHsK0p6Q", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Learning How to Build What's Next at Google Cloud On Board Brisbane", "Time Created": null, "Time Published": "2018-03-11T09:21:11Z", "Duration": null, "Description": "I spent the day learning about the Google Cloud Platform. Google is really stepping up their cloud game. Their goal is to make the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jHij_BJd8pc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Upper Body Calisthenics Workout in the Park", "Time Created": null, "Time Published": "2017-09-14T00:03:25Z", "Duration": null, "Description": "Upper Body Calisthenics Workout in the Park Dave and I have been working out outdoors lately instead at the gym. Our typical ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ssnyxrziCCQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Ego Versus Self", "Time Created": null, "Time Published": "2017-05-26T05:57:03Z", "Duration": null, "Description": "I started a Facebook page today. I'm continuing to try out new things. I was hesitant in making it though, I didn't know whether or ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "PJUGDwbPDw0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "A Template For Cold Emails - TDBS 25 April 2017", "Time Created": null, "Time Published": "2017-04-26T10:16:32Z", "Duration": null, "Description": "I plan on using this template in the near future! After reading around online, I've put together 5 points to think about when cold ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "U-OH0pyVdl0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "3 Life Principles I Learned From Ray Dalio", "Time Created": null, "Time Published": "2017-08-17T12:26:48Z", "Duration": null, "Description": "Ray Dalio is the founder of Bridgewater Associates, one of the largest hedge funds in the world. His net worth is somewhere ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wpw-xODKt4I", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Disagree and Commit, Words of Wisdom from Jeff Bezos - TDBS 19 April 2017", "Time Created": null, "Time Published": "2017-04-23T11:47:34Z", "Duration": null, "Description": "Disagree and Commit is a saying frequently used by Jeff Bezos. It's a way of making decisions faster. You can far too long being in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "94UCgt89G04", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Full body workout while my machine learning model trains (join in)", "Time Created": null, "Time Published": "2020-03-27T11:10:24Z", "Duration": null, "Description": "Join me doing a whole body bodyweight workout while my machine learning model trains. If you've ever trained a machine ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BFmAhK5OElI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "This Is Just The Beginning | TDBS Episode 100", "Time Created": null, "Time Published": "2017-06-14T09:57:33Z", "Duration": null, "Description": "Episode 100 of The Daniel Bourke Show! I was lucky enough to have 4 of my best friends as guests on this show. Be sure to listen ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "uaZauuHx5ko", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "It's Not All Sunshine", "Time Created": null, "Time Published": "2017-05-25T06:43:27Z", "Duration": null, "Description": "Today was an epic day. Some days are harder than others though. Daily challenge: Smile at yourself in the mirror for 10 seconds ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8fPj5XnPxKs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How do you know when to call it quits?", "Time Created": null, "Time Published": "2017-06-15T12:15:10Z", "Duration": null, "Description": "Day 92 of the original The Daniel Bourke Show 100-day series! Sometimes calling it a day is more courageous than continuing on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9eQMJF88bx4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Deep Learning on a WHITEBOARD and Udacity AI Nanodegree Progress! | Learning Intelligence 25", "Time Created": null, "Time Published": "2018-03-23T23:30:51Z", "Duration": null, "Description": "Progress has been made! I'm up to the NLP capstone project of the Udacity AI Nanodegree and I got a whiteboard to practice ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rqAqcFcfeK8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "TensorFlow for Deep Learning course Udemy launch Q&A (live)", "Time Created": null, "Time Published": "2021-04-30T03:11:36Z", "Duration": null, "Description": "Answering questions on TensorFlow for Deep Learning course (recently launched on Udemy)! Sign up for the course: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IqHInjrq0g8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Artificial Intelligence in Business Keynote at The University of Queensland", "Time Created": null, "Time Published": "2018-09-08T04:17:52Z", "Duration": null, "Description": "Athon and I went and presented a talk about how Max Kelsen have applied machine learning and artificial intelligence to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M2G3GINb4X4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Energising Wake Up Movement Session (bodyweight only)", "Time Created": null, "Time Published": "2020-03-31T10:42:29Z", "Duration": null, "Description": "This 10-minute energising bodyweight-only workout will wake you up and have you feeling better than when you started. Perfect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zPDxtFX5HeM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "MACHINE LEARNING IN 5 MINUTES", "Time Created": null, "Time Published": "2017-06-02T08:06:36Z", "Duration": null, "Description": "Recently I've been learning a whole bunch about Machine Learning. It's starting to take over the world of tech and it will slowly (or ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WHPl8wFk4kk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": ""Thank you" | Coronavirus 10-minute Bodyweight Bedroom Workout (follow along)", "Time Created": null, "Time Published": "2020-03-19T08:51:17Z", "Duration": null, "Description": "This 10-minute bodyweight workout can be performed anywhere, including your bedroom. Many countries are implementing ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "LJZIqYlKsWo", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Completing the Deeplearning.ai Specialization on Coursera | Learning Intelligence 18", "Time Created": null, "Time Published": "2018-01-24T11:38:05Z", "Duration": null, "Description": "Welcome to the eighteenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "WHPl8wFk4kk", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": ""Thank you" | Coronavirus 10-minute Bodyweight Bedroom Workout (follow along)", "Time Created": null, "Time Published": "2020-03-19T08:51:17Z", "Duration": null, "Description": "This 10-minute bodyweight workout can be performed anywhere, including your bedroom. Many countries are implementing ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "d6cwWRCysdI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Visual Introduction to Python List Comprehensions - Get the same done with less code", "Time Created": null, "Time Published": "2019-02-09T08:11:19Z", "Duration": null, "Description": "A brief introduction to list comprehensions in Python. Code on GitHub - http://bit.ly/pythonlistcomprehensioncode Article version of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Bm1gswXQAZs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Simple (but very difficult) Morning Home Workout", "Time Created": null, "Time Published": "2020-02-13T04:40:28Z", "Duration": null, "Description": "This simple yet effective morning home workout is helping Justin and I in the Brazilian Jiu-Jitsu arena, stay shredded and get ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wZMzzqpjqF0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Machine Learning and Movement Part 2", "Time Created": null, "Time Published": "2020-03-28T10:27:00Z", "Duration": null, "Description": "My machine learning model wasn't training and staring down the barrel of a CUDA error for 3-hours had me flattened out.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "u6-ljaw9j6k", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Self-taught Machine Learning Engineer AMA (live)", "Time Created": null, "Time Published": "2019-02-24T08:15:29Z", "Duration": null, "Description": "Ask Self-taught Machine Learning Engineer Daniel Bourke anything live. If you can't make the stream, the video will remain on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M2G3GINb4X4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "10-minute Energising Wake Up Movement Session (bodyweight only)", "Time Created": null, "Time Published": "2020-03-31T10:42:29Z", "Duration": null, "Description": "This 10-minute energising bodyweight-only workout will wake you up and have you feeling better than when you started. Perfect ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f9pztqE2QGM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Bayes Networks, Hidden Markov Models and How I Wake Up | Learning Intelligence 10", "Time Created": null, "Time Published": "2017-11-17T04:02:08Z", "Duration": null, "Description": "Welcome to the tenth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CvENLAzntlc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Data Engineering on Google Cloud Certification Progress | Learning Intelligence 48", "Time Created": null, "Time Published": "2018-12-21T13:15:23Z", "Duration": null, "Description": "I passed part four of the Data Engineering on Google Cloud Certification on Coursera! Google Data Engineering on Coursera ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "x0pu_nnW--s", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Train for the US Military fitness test in your bedroom (full body workout)", "Time Created": null, "Time Published": "2020-04-06T08:59:43Z", "Duration": null, "Description": "This full-body workout is based on the minimum fitness requirements to get into the US Military. Use it as a progression towards ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M1zYlTTC7aw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to be more self-reliant: The Jester Physicist Approach", "Time Created": null, "Time Published": "2020-05-31T13:15:01Z", "Duration": null, "Description": "Like spinning plates, self-reliance is an active process. But knowing the tools to maintain it is helpful. The Jester Physicist ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AXwALizB3rQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My first HACKATHON! | 100 Days of Code 1", "Time Created": null, "Time Published": "2017-05-18T00:02:40Z", "Duration": null, "Description": "I attended my first hackathon over the weekend! What an epic experience. I'm also trying to code every day for 100 days, let's see ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CbkUdSm3u0E", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "deeplearning.ai Sequence Models Course Progress | Learning Intelligence 21", "Time Created": null, "Time Published": "2018-02-17T17:30:00Z", "Duration": null, "Description": "Welcome to the twenty-first instalment of Learning Intelligence, in this episode I go through Part 5 of Andrew Ng's Deep Learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "7Bxn37QpHBc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "How to Pass the Turing Test + I FAILED | Learning Intelligence 6", "Time Created": null, "Time Published": "2017-10-19T00:38:52Z", "Duration": null, "Description": "How to Pass the Turing Test | Learning Intelligence 6 Welcome to episode 6 of the learning intelligence series! In this episode, I ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "wpw-xODKt4I", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Disagree and Commit, Words of Wisdom from Jeff Bezos - TDBS 19 April 2017", "Time Created": null, "Time Published": "2017-04-23T11:47:34Z", "Duration": null, "Description": "Disagree and Commit is a saying frequently used by Jeff Bezos. It's a way of making decisions faster. You can far too long being in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AGYYk3n0HoE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "HAPPY NEW YEAR! 4k Subscriber Q&A + My curriculum for 2019", "Time Created": null, "Time Published": "2019-01-13T12:33:26Z", "Duration": null, "Description": "I answered your questions on data science, machine learning, health and everything in between live on stream. If your question ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "sXKiG1DcKe8", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Ask a Machine Learning Engineer Anything (live) | April 2020", "Time Created": null, "Time Published": "2020-04-05T18:00:19Z", "Duration": null, "Description": "Machine Learning Engineer Daniel Bourke answers your questions about life, machine learning, business, getting a job and more ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "y_m3td1LF74", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Running a business from a bedroom - Ask me anything! (live)", "Time Created": null, "Time Published": "2019-11-17T01:50:50Z", "Duration": null, "Description": "I'm running an online business from home (making things in the machine learning and data science space), come and ask me ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "oAfkqHjLR_0", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "A Lesson In Movement | Raw Training Australia", "Time Created": null, "Time Published": "2017-04-23T22:16:00Z", "Duration": null, "Description": "I went and did a session with one of my good friends Jay at his gym, Raw Training Australia. As you'll see, I get schooled in a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jcTij0bYJsU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "MORE MACHINE LEARNING | 100 Days of Code 2", "Time Created": null, "Time Published": "2017-05-22T11:33:17Z", "Duration": null, "Description": "I passed my 2nd Machine Learning assignment on Coursera! This video is the 2nd instalment of my 100 days of code VLOG ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-oUyObRGu7M", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The Future is Looking Good | Daniel Bourke 2019 YouTube Trailer", "Time Created": null, "Time Published": "2019-01-20T00:36:31Z", "Duration": null, "Description": "My brother is practising video editing. He wanted to help me shoot a trailer for my channel. So we did. Thanks Wam! Get ready for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ahmlh7iBrxg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Building an Amazon Alexa Skill in a Day", "Time Created": null, "Time Published": "2018-09-22T23:15:13Z", "Duration": null, "Description": "Josh, Zenith and I decided to take on a challenge to build an Amazon Alexa Skill in a day. Alexa is a new platform so we're still ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Fl89dLBxpjc", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "PYTHON && POETRY | 100 Days of Code 16", "Time Created": null, "Time Published": "2017-08-19T04:56:27Z", "Duration": null, "Description": "I had my first shot at slam poetry this week! Although I'm learning how to code and about the world of computer science, I also like ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "f2qKMmkqGbI", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Kate O'Brien: Crack Yourself Open | The Daniel Bourke Show", "Time Created": null, "Time Published": "2017-08-21T09:36:03Z", "Duration": null, "Description": "Today I had the pleasure of talking with Kate O'Brien. Kate is one of Australasia's leading transformational coaches.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "CAFMh86Cv8A", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What\u2019s it like inside a $600,000,000 tech company? | Inside realestate.com.au - Part 2", "Time Created": null, "Time Published": "2018-07-01T10:24:22Z", "Duration": null, "Description": "I got a tour through one of Australia's biggest technology companies, REA Group. You can see Part 1 here: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TTkpbfghBBM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Passing Project 3 of Udacity's Artificial Intelligence Nanodegree | Learning Intelligence 9", "Time Created": null, "Time Published": "2017-11-09T05:52:53Z", "Duration": null, "Description": "Welcome to the ninth instalment of Learning Intelligence! A VLOG series where I document my journey learning about artificial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "04HX2zgQNXE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "1 week out from SPARTAN Race + How to bake a sweet potato in 5-minutes!", "Time Created": null, "Time Published": "2018-04-26T07:36:40Z", "Duration": null, "Description": "One of my last training sessions before hitting the Spartan Ultra! Spartan Ultra is the biggest Spartan Race available, 50km's of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "BeI0KQqgv3Y", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "GENERATING TV SCRIPTS WITH DEEP LEARNING | 100 Days of Code 7", "Time Created": null, "Time Published": "2017-06-14T09:39:54Z", "Duration": null, "Description": "I completed an interesting project recently, generating a TV script of a scene at Moe's Tavern from the Simpsons completely from ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "x_fx9yV4Seg", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "HOW (not) TO BUILD A PULL UP BAR", "Time Created": null, "Time Published": "2016-08-08T03:45:09Z", "Duration": null, "Description": "Joey and I woke up and decided to build a pull up bar in my backyard. After 5 separate trips to various hardware stores, we finally ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Tluc_B3oFBw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I'm Camera Shy - TDBS 17 April 2017", "Time Created": null, "Time Published": "2017-04-19T09:04:27Z", "Duration": null, "Description": "Recently I started recording the podcasts I make and turning them into YouTube videos. I'm still camera shy but I'm getting better ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "F4iq3gBMBqQ", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "GENERATING FACES WITH GANs | 100 Days of Code 14", "Time Created": null, "Time Published": "2017-08-04T23:16:44Z", "Duration": null, "Description": "My final project for the Udacity Deep Learning Nanodegree involved generating faces with GANs (Generative Adversarial ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IexHTrpEF_U", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "The War of Art & Facing Resistance", "Time Created": null, "Time Published": "2017-06-16T07:34:22Z", "Duration": null, "Description": "Day 90 of The Daniel Bourke Show original 100-day series. I started reading a book today called The War of Art. It has already ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "NFGQ6w7pab4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I'm Addicted to Learning - TDBS 28 April 2017", "Time Created": null, "Time Published": "2017-05-05T06:13:57Z", "Duration": null, "Description": "I don't know whether this is a good thing or a bad thing. Daily challenge: Learn something new! :D For more of me, check out: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "VaLnZ7QN5Xs", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Job Interview Tips and Open Ocean Swim | 100 Days of Code 4", "Time Created": null, "Time Published": "2017-05-29T11:39:35Z", "Duration": null, "Description": "My friend completed his first ever ocean swim over the weekend and I was so happy to be able to watch him. Be sure to check out ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ImWT7plGYBE", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Livestreaming Lessons, Building and Launching an App from Scratch and Google Duplex", "Time Created": null, "Time Published": "2018-05-17T11:21:16Z", "Duration": null, "Description": "Josh built his first app and launched it on the App Store! Will shares what he's learned switching from Twitch livestreaming to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "62818XFJQ0o", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Strong butt = good butt | 10-minute Glute Activating Workout (follow along)", "Time Created": null, "Time Published": "2020-03-29T09:09:49Z", "Duration": null, "Description": "Aside from having a triple-digit bench, I can't think of anything more important in life than having a good butt. This 10-minute home ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tZUm4tBNsCM", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "My First Time Speaking In Public - TDBS 20 April 2017", "Time Created": null, "Time Published": "2017-04-26T09:50:23Z", "Duration": null, "Description": "I gave my first ever public speech when I was 11 years old in 2004. It was called \"The Wacko Watch\". It was a smart watch (that ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "bw8fE_0dAkU", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "What I Would Do Differently At High School - TDBS 23 April 2017", "Time Created": null, "Time Published": "2017-04-26T09:55:47Z", "Duration": null, "Description": "I've recently been trying to triple down on the things that I'm good at, as well as at the same time trying to improve on things I'm ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "z5-oyanjRxw", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "I Want To Help 100,000 People Workout | AI Powered Personal Trainer", "Time Created": null, "Time Published": "2017-06-01T11:05:23Z", "Duration": null, "Description": "I built my first messenger bot today! It's an AI-based personal trainer that can help you workout. My overall goal is to help 100000 ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "I2xNf94Fjx4", "Channel ID": "UCr8O8l5cCX85Oem1d18EezQ", "Title": "Study with me: Data Science (25-minute session)", "Time Created": null, "Time Published": "2018-12-26T01:30:01Z", "Duration": null, "Description": "Studying can be tough. But you're not alone. I use the pomodoro technique (25-minutes of concentrated work, then a 5-minute ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xchDU2VMR4M", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Are Pre-trained Convolutions Better than Pre-trained Transformers? \u2013 Paper Explained", "Time Created": null, "Time Published": "2021-05-26T13:45:01Z", "Duration": null, "Description": "Paper explained and visualized \u201cAre Pre-trained Convolutions Better than Pre-trained Transformers?\u201d Tune in to the epic fight of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l3bTCP6x-FM", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "The efficiency misnomer | Size does not matter | What does the number of parameters mean in a model?", "Time Created": null, "Time Published": "2021-11-10T13:00:33Z", "Duration": null, "Description": "How important is the number of parameters in deep learning models? But what about other measures like FLOPs or ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "6BPl81wGGP8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "UMAP explained | The best dimensionality reduction?", "Time Created": null, "Time Published": "2021-02-18T13:00:01Z", "Duration": null, "Description": "UMAP explained! The great dimensionality reduction algorithm in one video with a lot of visualizations and a little code. Uniform ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DVoHvmww2lQ", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "An image is worth 16x16 words: ViT | Is this the extinction of CNNs? Long live the Transformer?", "Time Created": null, "Time Published": "2020-10-08T13:59:58Z", "Duration": null, "Description": "Mom, it's the Transformers again! They have come to ruin my CNN building blocks! An Image is Worth 16x16 Words: paper ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "me3UsMm9QEs", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "The ultimate intro to Graph Neural Networks. Maybe.", "Time Created": null, "Time Published": "2020-08-13T12:11:06Z", "Duration": null, "Description": "Ms. Coffee Bean appears with the definitive introduction to Graph Neural Networks! Or short: GNNs. Because graphs are ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "FWFA4DGuzSc", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "The Transformer neural network architecture EXPLAINED. \u201cAttention is all you need\u201d (NLP)", "Time Created": null, "Time Published": "2020-07-05T12:37:32Z", "Duration": null, "Description": "It is time to explain how Transformers work. If you are looking for a simple explanation, you found the right video! Table of ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1biZfFLPRSY", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Positional embeddings in transformers EXPLAINED | Demystifying positional encodings.", "Time Created": null, "Time Published": "2021-07-12T10:00:00Z", "Duration": null, "Description": "What are positional embeddings / encodings? Follow-up video: Concatenate or add positional encodings? Learned positional ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "SndHALawoag", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Swin Transformer paper animated and explained", "Time Created": null, "Time Published": "2021-09-28T13:00:24Z", "Duration": null, "Description": "Swin Transformer paper explained, visualized, and animated by Ms. Coffee Bean. Find out what the Swin Transformer proposes ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "iH-wmtxHunk", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "A brief history of the Transformer architecture in NLP", "Time Created": null, "Time Published": "2020-06-12T13:30:03Z", "Duration": null, "Description": "The Transformer architecture has revolutionized Natural Language Processing, being capable to beat the state-of-the-art on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "joZaCw5PxYs", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Beyond neural scaling laws \u2013 Paper Explained", "Time Created": null, "Time Published": "2022-09-10T08:00:16Z", "Duration": null, "Description": "Beyond neural scaling laws: beating power law scaling via data pruning\u201d paper explained with animations. You do not need to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "344w5h24-h8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Diffusion models explained. How does OpenAI's GLIDE work?", "Time Created": null, "Time Published": "2022-03-23T13:53:11Z", "Duration": null, "Description": "Diffusion models beat GANs in image synthesis, GLIDE generates images from text descriptions, surpassing even DALL-E in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Dp6iICL2dVI", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Masked Autoencoders Are Scalable Vision Learners \u2013 Paper explained and animated!", "Time Created": null, "Time Published": "2021-11-24T14:26:03Z", "Duration": null, "Description": "Masked Autoencoders Are Scalable Vision Learners\u201d paper explained by Ms. Coffee Bean. Say goodbye to contrastive learning ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "J87hffSMB60", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How does Stable Diffusion work? \u2013 Latent Diffusion Models EXPLAINED", "Time Created": null, "Time Published": "2022-08-31T09:22:57Z", "Duration": null, "Description": "StableDiffusion explained. How does an AI generate images from text? How do Latent Diffusion Models work? If you want ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-FbV2KgRM8A", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Data-efficient Image Transformers EXPLAINED! Facebook AI's DeiT paper", "Time Created": null, "Time Published": "2021-01-02T11:00:00Z", "Duration": null, "Description": "\"Training data-efficient image transformers & distillation through attention\" paper explained! How does the DeiT transformer for ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dqKM1Mbt0pU", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Linear algebra with Transformers \u2013 Paper Explained", "Time Created": null, "Time Published": "2021-12-22T12:30:23Z", "Duration": null, "Description": "Why would one build a transformer to solve linear algebra problems when there is numpy.linalg? Check out the video to find out ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "3AUfWllnO7c", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "PCA explained with intuition, a little math and code", "Time Created": null, "Time Published": "2020-12-09T11:00:01Z", "Duration": null, "Description": "Say \"PCA\" and the dimensions go away! Dimensionality reduction with PCA (Principal Component Analysis) explained with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dh8Rxhf7cLU", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "OpenAI\u2019s CLIP explained! | Examples, links to code and pretrained model", "Time Created": null, "Time Published": "2021-01-26T12:00:09Z", "Duration": null, "Description": "Ms. Coffee Bean explains \u2753 how OpenAI's CLIP works, \u2754 what it can and cannot do \u2049\ufe0f and what people have been up to using ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "M2ToEXF6Olw", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Adding vs. concatenating positional embeddings & Learned positional encodings", "Time Created": null, "Time Published": "2021-07-18T11:45:01Z", "Duration": null, "Description": "When to add and when to concatenate positional embeddings? What are arguments for learning positional encodings? When to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "QqejV0LNDHA", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "ConvNeXt: A ConvNet for the 2020s \u2013 Paper Explained (with animations)", "Time Created": null, "Time Published": "2022-01-26T14:00:11Z", "Duration": null, "Description": "Can a ConvNet outperform a Vision Transformer? What kind of modifications do we have to apply to a ConvNet to make it as ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "j7pWPdGEfMA", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "FNet: Mixing Tokens with Fourier Transforms \u2013 Paper Explained", "Time Created": null, "Time Published": "2021-05-20T08:30:09Z", "Duration": null, "Description": "Ms. Coffee Bean explains and visualizes the paper \"FNet: Mixing Tokens with Fourier Transforms\" and what it all has to do with .", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4v7ngaiFdp4", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "The curse of dimensionality. Or is it a blessing?", "Time Created": null, "Time Published": "2020-12-02T11:00:03Z", "Duration": null, "Description": "MachineLearning often deals with high dimensional data or representations. Are many dimensions a blessing or a curse?", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YyTyWGUUhmo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Adversarial Machine Learning explained! | With examples.", "Time Created": null, "Time Published": "2020-07-24T13:00:18Z", "Duration": null, "Description": "Hint: Stay until the end of the video for an adversarial attack compilation! Ever wondered what adversarial attacks are?", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yi-A0kWXEO4", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "PaLM Pathways Language Model explained | 540 Billion parameters can explain jokes!?", "Time Created": null, "Time Published": "2022-04-26T13:18:50Z", "Duration": null, "Description": "It's time to explain PaLM, Google AI's Pathways Language model in a coffee break! \u2615 Are you ready for this 540 billion dense ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Xxts1ithupI", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Do Transformers process sequences of FIXED or of VARIABLE length? | #AICoffeeBreakQuiz", "Time Created": null, "Time Published": "2021-10-31T13:00:13Z", "Duration": null, "Description": "Explaining the answer to the following AI Coffee Break Quiz question: \u201cDo Transformers process sequences of fixed or of variable ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yPXNQ6Ig7hQ", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "[Quiz] Eigenfaces, Domain adaptation, Causality, Manifold Hypothesis, Denoising Autoencoder", "Time Created": null, "Time Published": "2021-12-26T13:00:34Z", "Duration": null, "Description": "Machine Learning Quiz questions explained. Luckily, Ms. Coffee Bean found Tim Elsner @daidailoh (Twitter) \u201cbrave\u201d enough to ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "P23EWdiPWDw", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Multimodal Machine Learning models do not work. Here is why. Part 1/2 \u2013 The SYMPTOMS", "Time Created": null, "Time Published": "2020-09-17T11:00:09Z", "Duration": null, "Description": "Have you ever wondered where the problems with multimodal integrations of vision and language are? This is the first part of Ms.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-GH9vW5FWUs", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Generalization \u2013 Interpolation \u2013 Extrapolation in Machine Learning: Which is it now!?", "Time Created": null, "Time Published": "2021-10-27T10:00:01Z", "Duration": null, "Description": "A summary of the Generalization \u2013 Interpolation \u2013 Extrapolation debate in machine Learning. \u201cLearning in High Dimension ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "zAyDhZFup9k", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "[Quiz] Regularization in Deep Learning, Lipschitz continuity, Gradient regularization", "Time Created": null, "Time Published": "2022-04-05T10:30:08Z", "Duration": null, "Description": "Regularization, Lipschitz continuity, Gradient regularization, Adversarial Defense, Gradient Penalty, were all topics of our daily ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xqDeAz0U-R4", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Imagen, the DALL-E 2 competitor from Google Brain, explained \ud83e\udde0| Diffusion models illustrated", "Time Created": null, "Time Published": "2022-05-30T18:48:26Z", "Duration": null, "Description": "Imagen from Google Brain is competing with DALLE-2 when it comes to generating amazing images from just text! Here is an ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "pFf4PltQ9LY", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "BERTology meets Biology | Solving biological problems with Transformers", "Time Created": null, "Time Published": "2020-08-01T17:27:08Z", "Duration": null, "Description": "Transformers are meanwhile famous in natural language processing. New research applies the BERT Transformer architecture ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "YkK5IKgxp-c", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How modern search engines work \u2013 Vector databases explained! | Weaviate open-source", "Time Created": null, "Time Published": "2021-09-05T12:00:30Z", "Duration": null, "Description": "Modern search engines explained. What you need to know about today's vector search engines, explained on a high-level with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dd7nE4nbxN0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Transformer combining Vision and Language? ViLBERT - NLP meets Computer Vision", "Time Created": null, "Time Published": "2020-07-11T16:48:33Z", "Duration": null, "Description": "If you always wanted to know hot to integrate both text and images in one single MULTIMODAL Transformer, then this is the video ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jReaoJWdO78", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "What nobody tells you about MULTIMODAL Machine Learning! \ud83d\ude4a THE definition.", "Time Created": null, "Time Published": "2020-09-03T11:11:44Z", "Duration": null, "Description": "Multimodality \u2013 a definition. Parcalabescu et al. \"What is Multimodality?\" (2021): https://arxiv.org/abs/2103.06304 What is ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XU4ZHUnnbpg", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "SimVLM explained | What the paper doesn\u2019t tell you", "Time Created": null, "Time Published": "2021-10-20T12:00:15Z", "Duration": null, "Description": "SimVLM explained. What the authors tell us, what they don't tell us and how this all works. Enjoy with coffee! Vision ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "D8j1c4NJRfo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "What is tokenization and how does it work? Tokenizers explained.", "Time Created": null, "Time Published": "2021-08-23T14:51:44Z", "Duration": null, "Description": "What is tokenization? Ms. Coffee Bean explains tokenization (highly relevant for transformers nowadays) and highlights the ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "_qB4B6ttXk8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "GANs explained | Generative Adversarial Networks video with showcase!", "Time Created": null, "Time Published": "2020-08-27T11:00:10Z", "Duration": null, "Description": "Generative Neural Networks (GANs) explained for everybody. We also have a little compilation of 5 examples of what GANs can ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "-niprVHNrgI", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "AI understanding language!? A roadmap to natural language understanding.", "Time Created": null, "Time Published": "2020-10-20T11:45:00Z", "Duration": null, "Description": "What does it take to make a Machine Learning system understand natural language? \"Experience Grounds Language\" \u2013 Paper ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "aH7s6qXEUcc", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Transformers can do both images and text. Here is why.", "Time Created": null, "Time Published": "2021-02-08T12:30:02Z", "Duration": null, "Description": "What are the differences between text and images? Why can neural networks process both? This video explains why ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XHAoV_nKr1o", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "SEER explained: Vision Models more Robust & Fair when pretrained on UNCURATED images!?", "Time Created": null, "Time Published": "2022-04-12T10:45:00Z", "Duration": null, "Description": "The 10 billion parameter SEER model from @MetaAI is *fairer*, even though it is trained on *uncurated* data. How so? Check out ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "IOgxsULnqUo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "NVIDIA Jarvis (now NVIDIA Riva) meets Ms. Coffee Bean", "Time Created": null, "Time Published": "2021-02-25T16:00:13Z", "Duration": null, "Description": "Ms. Coffee Bean meets NVIDIA Jarvis (recently renamed to Nvidia Riva). This is how it went.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "4Cxz4rnnZ7Q", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Foundation Models | On the opportunities and risks of calling pre-trained models \u201cFoundation Models\u201d", "Time Created": null, "Time Published": "2021-09-01T10:30:00Z", "Duration": null, "Description": "Sound the opinionated video alarm! We need to talk about \u201cfoundation models\u201d: What does the term mean? Is ViT a foundation ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "jlmH1PAI6oU", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": ""Please Commit More Blatant Academic Fraud" \u2013 A fellow PhD student's response.", "Time Created": null, "Time Published": "2021-06-01T09:35:43Z", "Duration": null, "Description": "A broadcast of, discussion and response to \"Please Commit More Blatant Academic Fraud\" blog post by Jacob Buckman. Made by ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "DwaBQbqh5aE", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Self-Attention with Relative Position Representations \u2013 Paper explained", "Time Created": null, "Time Published": "2021-07-31T18:15:49Z", "Duration": null, "Description": "We help you wrap your head around relative positional embeddings as they were first introduced in the \u201cSelf-Attention with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "P7Rav5tK3Y0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Pattern Exploiting Training explained! | PET, iPET, ADAPET", "Time Created": null, "Time Published": "2021-04-02T11:43:17Z", "Duration": null, "Description": "Small language models are also few-shot learners! Here you can find all about PET, iPET, ADAPET. Choose your favorite!", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mvG2FGF0TvM", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "OpenAI's DALL-E explained. How GPT-3 creates images from descriptions.", "Time Created": null, "Time Published": "2021-01-06T17:48:37Z", "Duration": null, "Description": "How can GPT-3 create an avocado armchair? Have a look at DALL\u00b7E, OpenAI's new amazing text-to-image generator. Video with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dOwRXpSSc8E", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How do Vision Transformers work? \u2013 Paper explained | multi-head self-attention & convolutions", "Time Created": null, "Time Published": "2022-02-23T13:47:26Z", "Duration": null, "Description": "It turns out that multi-head self-attention and convolutions are complementary. So, what makes multi-head self-attention different ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "dabFOBE4eZI", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Pre-training of BERT-based Transformer architectures explained \u2013 language and vision!", "Time Created": null, "Time Published": "2020-07-15T17:58:33Z", "Duration": null, "Description": "What is masked language modelling? Or next sentence prediction? And why are they working so well? If you ever wondered what ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yhVlb-Hz6yM", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Leaking training data from GPT-2. How is this possible?", "Time Created": null, "Time Published": "2021-01-10T14:03:12Z", "Duration": null, "Description": "Ms. Coffee Bean explains how a huge collaboration of researchers managed to extract training data from large language models ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "5fqxPOaaqi0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "GPT-3 explained with examples. Possibilities, and implications.", "Time Created": null, "Time Published": "2020-07-22T19:28:22Z", "Duration": null, "Description": "What is going on in AI research lately? GPT-3 crashed the party, let's see what it is and what it can do. Hoping we do not forget ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "humlomyUB_Q", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "[Own work] VALSE \ud83d\udc83: Benchmark for Vision and Language Models Centered on Linguistic Phenomena", "Time Created": null, "Time Published": "2022-05-03T12:00:41Z", "Duration": null, "Description": "Let's VALSE ! We present our own work on the VALSE benchmark testing large pretrained vision and language models by ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "R80kc5cwEUw", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Can a language model (like GPT-3) learn meaning? But really?", "Time Created": null, "Time Published": "2020-08-20T11:30:02Z", "Duration": null, "Description": "What is meaning? How far is state-of-the art NLP from meaning? Do publications misuse the word \u201cmeaning\u201d? \"Climbing towards ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "xqdHfLrevuo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "[RANT] Adversarial attack on OpenAI\u2019s CLIP? Are we the fools or the foolers?", "Time Created": null, "Time Published": "2021-03-18T13:00:26Z", "Duration": null, "Description": "Pen and paper fool OpenAI!\u201d Typographic attacks in the wild. Or not. Ms. Coffee Bean rants about the typographic attacks on ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "fL22NAtMNYo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How to check if a neural network has learned a specific phenomenon?", "Time Created": null, "Time Published": "2020-05-31T09:26:21Z", "Duration": null, "Description": "In this video, Ms. Coffee Bean and I explain how \"probing\" neural networks (in NLP) works. In other words, how we check if a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "AcvmyqGgMh8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How to make Movies with diffusion | Make-a-Video from MetaAI and Imagen Video from Google Brain", "Time Created": null, "Time Published": "2022-10-10T12:11:46Z", "Duration": null, "Description": "Video Diffusion models explained: MetaAI's Make-a-Video diffusion model and Imagen Video from Google Research. Sponsor: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8_UBDTHAHqY", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Data leakage during data preparation? | Using AntiPatterns to avoid MLOps Mistakes", "Time Created": null, "Time Published": "2021-08-10T10:00:08Z", "Duration": null, "Description": "How can data leakage happen during data preparation? Find out here, where Ms. Coffee Bean is visualizing the answer to this ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "MNwURQ9621k", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "DALLE-2 has a secret language!? | Theories and explanations", "Time Created": null, "Time Published": "2022-06-13T12:39:15Z", "Duration": null, "Description": "DALLE-2 has a secret language? No, it's rather a secret vocabulary. Let's see what happens and why the model behaves like this.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "KS7UlN9SCg4", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "[Quiz] Interpretable ML, VQ-VAE w/o Quantization / infinite codebook, Pearson\u2019s, PointClouds", "Time Created": null, "Time Published": "2022-01-05T12:45:00Z", "Duration": null, "Description": "A hot batch of #MachineLearning Quiz questions explained! Tim Elsner @daidailoh (Twitter) jumped in again to do Ms. Coffee ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ytxnTwHfWls", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How cross-modal are vision and language models really? \ud83d\udc40 Seeing past words. [Own work]", "Time Created": null, "Time Published": "2021-06-14T11:00:23Z", "Duration": null, "Description": "What could go wrong when presenting a paper without Ms. Coffee Bean? And this time, it is not ANY paper : Paper: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "KDCKJkNpMGQ", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "The convolution is not shift invariant. | Invariance vs Equivariance | \u2753 #AICoffeeBreakQuiz #Shorts", "Time Created": null, "Time Published": "2021-08-21T13:00:08Z", "Duration": null, "Description": "Are convolutions translational invariant? No, they're translation equivariant. What is the difference between invariance and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "9puivTkDaQk", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Why Multimodal Machine Learning models do not work. Part 2/2 \u2013 The CAUSES", "Time Created": null, "Time Published": "2020-09-24T10:15:00Z", "Duration": null, "Description": "Do you want to know the REASONS for problems in integrating images and text with deep learning? This is the second part of a ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "m2bXL5Z5CBM", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "A New Physics-Inspired Theory of Deep Learning | Optimal initialization of Neural Nets", "Time Created": null, "Time Published": "2022-05-12T12:00:36Z", "Duration": null, "Description": "A special video about recent exciting developments in mathematical deep learning! Make sure to check out the video if you ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "y7HivfXcMx0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "How to increase the receptive field in CNNs? | #AICoffeeBreakQuiz #Shorts", "Time Created": null, "Time Published": "2021-08-22T12:15:51Z", "Duration": null, "Description": "Why network depth increases the receptive field / context window in Convolutional Neural Networks (CNNs). Explained and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "l7ofrfmVsd0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Deep Learning for Symbolic Mathematics!? | Paper EXPLAINED", "Time Created": null, "Time Published": "2021-04-13T12:44:35Z", "Duration": null, "Description": "\"Neural Nets are inexact beasts that will never solve exact problems\", right? Wrong. Ms. Coffee Bean explains, draws and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "yCSXASFWNgA", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Eyes tell all: How to tell that an AI generated a face?", "Time Created": null, "Time Published": "2021-09-09T10:21:23Z", "Duration": null, "Description": "Are you afraid you cannot tell Deepfakes apart from real images? What if we told you that there is a way to know whether a face ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "1gHUiNLYa20", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Machine Translation for a 1000 languages \u2013 Paper explained", "Time Created": null, "Time Published": "2022-07-18T11:48:40Z", "Duration": null, "Description": "We explain the new polyglot model from Google Research that can translate between 1000 languages! No need to read the long ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "debgj24BAZE", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Charformer: Fast Character Transformers via Gradient-based Subword Tokenization +Tokenizer explained", "Time Created": null, "Time Published": "2021-06-29T10:43:54Z", "Duration": null, "Description": "What is tokenization? Ms. Coffee Bean explains tokenization in general, explains why flexible tokenization is important and then ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "mI4sXRSkzE8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "What is the model identifiability problem? | Explained in 60 seconds! | \u2753 #AICoffeeBreakQuiz #Shorts", "Time Created": null, "Time Published": "2021-08-05T16:08:49Z", "Duration": null, "Description": "What is model (non)identifiability? Discussed AI Coffee Break Quiz questions: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "a6sKYiGMuXc", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Is today's AI smarter than YOU? #Shorts", "Time Created": null, "Time Published": "2021-08-16T13:58:09Z", "Duration": null, "Description": "The shortest and most honest explanation about the current state of today's Artificial Intelligence, or rather: When is your iPhone ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "TchiNj-BMtY", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "GPT2 wrote this 1000 subscribers special!", "Time Created": null, "Time Published": "2020-11-08T13:56:38Z", "Duration": null, "Description": "An AI wrote the script of this video. Thanks to everyone for your support! 1000 is an incredibly high number for people to follow ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "XEJ12DYtlOg", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Convolution vs Cross-Correlation. How most CNNs do not compute convolutions. | \u2753 #Shorts", "Time Created": null, "Time Published": "2021-08-19T13:24:21Z", "Duration": null, "Description": "Most CNNs do not compute convolutions, but cross-correlations. This is how, in 60 seconds. Our Veritasium Contest ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gzNlfvu1hqo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Announcement: \u2615\u2694\ufe0f\ud83c\udf75 AMA with AI Coffee Break & Chai Time Data Science over @Weights & Biases #Shorts", "Time Created": null, "Time Published": "2022-02-22T16:36:43Z", "Duration": null, "Description": "Watch on YouTube: https://www.youtube.com/watch?v=h0u64iBR1EI Happened on the 26th of Feb. at 5 PM CET / 8 AM PT.", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "W57u1j16iC8", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Data BAD | What Will it Take to Fix Benchmarking for NLU?", "Time Created": null, "Time Published": "2021-10-10T12:00:12Z", "Duration": null, "Description": "The Coffee Bean explains and comments the sobering take of the paper \"What Will it Take to Fix Benchmarking in Natural ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "rbg1Mdo2LZM", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Can a neural network tell if an image is mirrored? \u2013 Visual Chirality", "Time Created": null, "Time Published": "2020-08-08T09:18:39Z", "Duration": null, "Description": "What if a neural network can tell if an image is mirrored or not? How can image flipping and mirroring affect data augmentation in ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "h9xPrgTYP_0", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "AI Coffee Break - Channel Trailer", "Time Created": null, "Time Published": "2020-05-31T09:11:54Z", "Duration": null, "Description": "This is a YouTube Series about recent and relevant AI papers and topics. And Miss. Coffee Bean is kind enough to help me with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "Ev17hz52FGo", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Our paper at CVPR 2020 - MUL Workshop and ACL 2020 - ALVR Workshop", "Time Created": null, "Time Published": "2020-06-22T13:49:59Z", "Duration": null, "Description": "We are happy to share with you our presentation of our new paper where we propose unsupervised phrase grounding that ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "ttDkpIq-sD4", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": ""What Can We Do to Improve Peer Review in NLP?" \ud83d\udc40", "Time Created": null, "Time Published": "2020-11-24T12:00:23Z", "Duration": null, "Description": "\"What Can We Do to Improve Peer Review in NLP?\" by A. Rogers and I. Augenstein explained by Ms. Coffee Bean! Enjoy! ... and ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "gx8ojvWV0jI", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Why do we care about cross-correlations vs convolutions | \u2753 #AICoffeeBreakQuiz #Shorts", "Time Created": null, "Time Published": "2021-08-20T10:56:06Z", "Duration": null, "Description": "How replacing the convolution by the cross-correlation loses the commutative property. Our Veritasium Contest submission: ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "tx6aXnt47po", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Scaling Vision Transformers? How much data can a transformer get? #Shorts", "Time Created": null, "Time Published": "2021-06-09T19:19:59Z", "Duration": null, "Description": "shorts Ms. Coffee Bean is shocked by the scaling laws of transformers on images (or ViT at least). Discussed paper : \u201cScaling ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "noxb_1zpDIw", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Saddle points vs. local minima in high dimensional spaces | \u2753 #AICoffeeBreakQuiz #Shorts", "Time Created": null, "Time Published": "2021-08-04T10:00:17Z", "Duration": null, "Description": "What are more common in high dimensional spaces? Local minima or saddle points? And why? #shorts #AICoffeeBreak ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "b6Gad5edd18", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Preparing for Virtual Conferences \u2013 7 Tips for recording a good conference talk", "Time Created": null, "Time Published": "2020-07-06T08:47:22Z", "Duration": null, "Description": "Online talks, virtual Conferences. They put us in the position to do what we have not done before, which is giving a pre-recorded ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "HWna2c5VXDg", "Channel ID": "UCobqgqE4i5Kf7wrxRxhToQA", "Title": "Transformer in Transformer: Paper explained and visualized | TNT", "Time Created": null, "Time Published": "2021-03-02T20:29:23Z", "Duration": null, "Description": "Transformer in Transformer\u201d paper explained by Ms. Coffee Bean. In this video you will find out why modelling image patches with ...", "Category": null, "Like Count": NaN, "Dislike Count": NaN}
{"Video ID": "8yJ2kmqECsU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro vs M1 Max iOS Simulator Performance", "Time Created": null, "Time Published": "2021-11-06T18:23:04Z", "Duration": null, "Description": "Native Apple software at work on the new M1 Pro vs M1 Max MacBooks testing the iOS build and simulator startup speed.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "p-T0a_ZS8Yw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "big tech or free(lance)?", "Time Created": null, "Time Published": "2022-01-28T18:33:54Z", "Duration": null, "Description": "Why would anyone want to work at a big tech company in 2022? There are some benefits. I've been a freelancing consulting ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "XxJtjoDhV6o", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your JavaScript sort is kinda slow", "Time Created": null, "Time Published": "2021-10-05T13:14:50Z", "Duration": null, "Description": "JavaScript's built-in sort function is SLOW! Here are 3 ways to sort numbers, some of which will be much faster, depending on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "R2KkJ_Zawnk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I had no idea you could do this - MacOS using React?", "Time Created": null, "Time Published": "2022-03-11T18:37:28Z", "Duration": null, "Description": "Jim Nielsen's blog post: https://blog.jim-nielsen.com/2022/inspecting-web-views-in-macos NativeScript training courses ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "k7Y9c-T8uDk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "what's causing the M1 CPU to spike?", "Time Created": null, "Time Published": "2022-04-05T19:31:46Z", "Duration": null, "Description": "Why use/not use ripgrep: https://blog.burntsushi.net/ripgrep #ripgrep #vscode NativeScript training courses ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Y3u0ffqcZLg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Increase Your Productivity as a Software Developer or Learning Programming \ud83e\udd13", "Time Created": null, "Time Published": "2022-05-31T15:53:52Z", "Duration": null, "Description": "I've been experimenting with improving my productivity as a software developer. In this video I share what I see working for me.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ub2Osa77Cv0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple's messed up - YOU WIN!", "Time Created": null, "Time Published": "2022-05-03T14:48:15Z", "Duration": null, "Description": "Out of all the laptops that Apple released since it introduced Apple Silicon with the M1 chips in 2020, this one is the highlight, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TDEVWLHcDgM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "REACT NativeScript: First Look!", "Time Created": null, "Time Published": "2019-09-20T19:16:20Z", "Duration": null, "Description": "Well it's finally ready! After months and months of waiting, React NativeScript is the missing link that's now ripe and ready to be ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PPYi2PzeVAM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs 2015 MacBook Pro Node Stress Test", "Time Created": null, "Time Published": "2021-01-21T19:52:02Z", "Duration": null, "Description": "Another fun little throwback test, this time covering the performance of the new Apple M1 MacBook Air in a NodeJS Stress test, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ndm9XKzIENc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Lenovo developer laptops 2022 are ... different", "Time Created": null, "Time Published": "2022-01-09T15:21:00Z", "Duration": null, "Description": "Some strange, but perhaps useful Lenovo laptops coming in 2022. Lenovo ThinkBook Plus Gen 3 - a weird monster. Lenovo ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "SeTol800wFQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Bottom Sheet in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-06-20T12:49:55Z", "Duration": null, "Description": "By popular request, in this NativeScript tutorial I create an animated bottom sheet that works on iOS and Android. I use the multiple ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "IIX8euLFnSI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I got BANNED by Stack Overflow doing M1 Pro/Max tests", "Time Created": null, "Time Published": "2021-11-12T15:00:19Z", "Duration": null, "Description": "While doing a commenter requested test comparing the M1 with M1 Pro and M1 Max MacBooks, I got myself blocked by Stack ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NXi2o0_JNqg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "returning macbook pro (m1 pro)", "Time Created": null, "Time Published": "2022-03-16T11:19:03Z", "Duration": null, "Description": "I'm returning the MacBook Pro with the M1 Pro chip - and thanks to the channel members! \u25b6\ufe0fMy recent tests of M1 Pro/Max ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "k9cxGlAlo4s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Recreating the Spotify App Artist Page in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-09-17T21:07:53Z", "Duration": null, "Description": "I always liked using the Spotify app - there's just something about it that flows well, especially the sticky, large, green play button.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mC8CUNFfiCU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I build the quietest PC using APPLE SILICON!", "Time Created": null, "Time Published": "2022-04-01T13:06:45Z", "Duration": null, "Description": "macstudio #m1ultra #m1.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "eK_SRVRO-Xo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Pro Shortcomings | Reaction", "Time Created": null, "Time Published": "2022-02-25T16:04:02Z", "Duration": null, "Description": "My reaction to some unique findings about the latest MacBook Pros by another YouTuber. \u25b6\ufe0f it's ugly, but I picked it anyway ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8zU_oEH5dWM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i9 in Continuous TypeScript Build Test - Dell with Intel i7 the Real Winner", "Time Created": null, "Time Published": "2021-01-11T16:14:31Z", "Duration": null, "Description": "As we keep rolling with the series about M1 for developers, there is a new contender that enters the ring: Dell XPS 13. Nope, it's ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "c7PEuIKGGiY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Force Component Destroy by Using Page Life Cycle in NativeScript Angular Tutorial", "Time Created": null, "Time Published": "2019-05-01T12:34:23Z", "Duration": null, "Description": "NativeScript Angular keeps navigated components alive on a stack. This is great for performance, since the framework doesn't ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Oiq4dZbXVWA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "you'll always be inferior", "Time Created": null, "Time Published": "2022-07-19T15:20:40Z", "Duration": null, "Description": "I'm reading \"Courage to be Disliked\" by Fumitake Koga and Ichiro Kishimi and here's what I got from the book as it relates to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Q3vb1w7Uv1Q", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air Cooling | YouTubers Outsmart Apple Engineers?", "Time Created": null, "Time Published": "2022-08-08T11:52:11Z", "Duration": null, "Description": "Let's discuss cooling your M2 MacBook Air, and try one of the techniques. Cooling pad: https://amzn.to/3p5uoLr Run Windows on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "gmCpp9YINzM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Hacking a multi-core #webapp TEST \ud83c\udfc1", "Time Created": null, "Time Published": "2022-04-29T15:22:01Z", "Duration": null, "Description": "Speedometer tests web application speed, but only on one browser tab at a time, and thus using only one CPU core (sort of).", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "LHYkoUNXMJ0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Floating Action Button in NativeScript with Angular. Part 4: Adding the Finishing Touches", "Time Created": null, "Time Published": "2017-01-26T13:40:48Z", "Duration": null, "Description": "Finally, in part 4 of the tutorial, you will make the user feel like they are actually tapping on a button. I show you how to use ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZEnAyTi1uIQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Visual Studio 2022 for ARM coming soon!", "Time Created": null, "Time Published": "2022-05-24T19:55:28Z", "Duration": null, "Description": "A surprise announcement from Microsoft CEO Satya Nadella today at the Build developer conference. Grab Parallels for yourself: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NM-aab5GpKo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Fastest way to build a monorepo | Turborepo vs Nx", "Time Created": null, "Time Published": "2021-12-21T15:39:12Z", "Duration": null, "Description": "Turborepo is a new player in the town of monorepos. Let's run a benchmark that pins build performance of Nx to Turborepo.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "05XoA7IhTp8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra vs Intel PC and Docker", "Time Created": null, "Time Published": "2022-03-30T15:32:24Z", "Duration": null, "Description": "In this video I take a look at Docker for Apple Silicon M1 Ultra. I perform a build speed test on a real project, and then on a large ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Lrx06mh7YAc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "2 Methods to Simulate a Slow Network Connection for iOS and Android Development", "Time Created": null, "Time Published": "2020-11-18T16:30:01Z", "Duration": null, "Description": "In this video I'll show you how to set up two tools for helping to simulate a slow network connection when you're developing ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "2I835GG8u7c", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Node Side by Side Performance Test", "Time Created": null, "Time Published": "2021-02-25T14:51:00Z", "Duration": null, "Description": "In this video, I'm doing a side by side TypeScript build test of Node for ARM and Node for x86 running via Rosetta on the new M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Pyio2yuKxzQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Keep your\ud83d\udcb2 and the M1 MacBook Air? | REAL JavaScript Shootout vs M1 Pro", "Time Created": null, "Time Published": "2021-11-18T15:06:52Z", "Duration": null, "Description": "In this video I compare the build speeds on the M1 MacBook Air machine vs the new 14\" MacBook Pro with the M1 Pro chip, using ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rskUWZi3pyQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Exploring NativeScript Plugins: Numeric Keyboard", "Time Created": null, "Time Published": "2020-06-26T16:45:01Z", "Duration": null, "Description": "In this first of the NativeScript plugins series, I show you how to set up an input to display a numeric keyboard instead of the usual ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qgwdN97LANo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Floating Action Button in NativeScript with Angular. Part 2: Creating and Styling the FAB Component", "Time Created": null, "Time Published": "2017-01-26T13:38:04Z", "Duration": null, "Description": "In part 2 of this tutorial, I show you how to create and style the actual floating action button component. Don't skip part 1 though ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "zhXsMlv_4Ik", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Macbook vs Intel EVO Ideapad for Android Development?", "Time Created": null, "Time Published": "2021-03-26T14:26:49Z", "Duration": null, "Description": "In this video I test the Lenovo IdeaPad Slim 9 with an Intel i7 11th Generation processor. I build an Android benchmark project ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dkovK_eq6eg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Which M1 Pro/Max for which Programmer?", "Time Created": null, "Time Published": "2021-12-30T15:27:46Z", "Duration": null, "Description": "The new M1 Pro and M1 Max MacBook pros are among some of the options if you're a software developer, but they aren't the only ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "1f_ahSt_UI0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "OpenCV Build SLOW? Make it faster!", "Time Created": null, "Time Published": "2021-04-16T14:00:01Z", "Duration": null, "Description": "OpenCV building slow for you? This video shows off some native builds at work on the new M1 MacBook Air (16Gb model) as ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Y_yPZj4WYeQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": ".NET MAUI no love for Mac users", "Time Created": null, "Time Published": "2022-04-13T19:08:25Z", "Duration": null, "Description": "what's up with dotnet Maui release candidate and not supporting iOS? #maui #dotnet #shorts.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "63_lB0mB6O0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Does Intel i9 beat the M1 in Android Studio build?", "Time Created": null, "Time Published": "2021-08-19T16:39:20Z", "Duration": null, "Description": "How much faster will running Android Studio with Apple Silicon support be compared to running the same large app build on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-kgNeyZNatk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Github Copilot has a HIDDEN SKILL", "Time Created": null, "Time Published": "2021-07-06T14:00:00Z", "Duration": null, "Description": "Taking Github Copilot out for a spin, which is an AI (OpenAI GPT-3) powered tool that can write code for you automatically in many ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "sIj2GSGu_TQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel FIGHTS back! | End of the M1?", "Time Created": null, "Time Published": "2022-01-06T14:59:26Z", "Duration": null, "Description": "Good stuff coming from Intel in 2022. Is it time to reconsider getting an M1 MacBook and instead wait a little bit for the new PC ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xQgYhNnuQBU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac guy forced to buy Windows laptop for software dev", "Time Created": null, "Time Published": "2022-05-19T14:48:33Z", "Duration": null, "Description": "I love my MacBook Pro, but I HAVE to get a Windows/Linux laptop for software development. Here are the things I look for in a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tf4gRH_tEv8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Android Studio on Apple Silicon is HOW FAST?", "Time Created": null, "Time Published": "2021-08-11T13:18:39Z", "Duration": null, "Description": "How much faster will running Android Studio with Apple Silicon support be compared to running the same large app build on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BLzz2XEdHZ8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I used the Mac Studio Ultra for 1 month!", "Time Created": null, "Time Published": "2022-05-10T15:04:29Z", "Duration": null, "Description": "I've been using the Mac Studio with the M1 Ultra for over a month now, but I haven't yet put aside my MacBook Pro with the M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pKCrZEzuALA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Which .NET on a Mac type are you?", "Time Created": null, "Time Published": "2022-01-27T13:22:55Z", "Duration": null, "Description": "dotnet, or .NET as it's been known from time to time, has grown into a nice cross platform framework that even runs natively on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PxM3w0qjelc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Programming on a gaming laptop", "Time Created": null, "Time Published": "2022-02-17T19:26:49Z", "Duration": null, "Description": "Here's what I look for when programming on a gaming laptop. \u25b6\ufe0fMy recent tests of M1 Pro/Max MacBooks for Developers ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "WcT0IBHF5nE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "i tried programming on the CHEAPEST laptop", "Time Created": null, "Time Published": "2022-05-24T18:37:18Z", "Duration": null, "Description": "I wanted to see what the developer experience would be like on a really cheap laptop - is it even possible? Cheap laptop that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "o4diDh7f2Dk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra is fast, but is Intel 12th Gen faster?", "Time Created": null, "Time Published": "2022-03-27T20:02:06Z", "Duration": null, "Description": "Testing the Mac Studio M1 Ultra against the Intel Core i9 (12900KF) in Chrome to see web test scores in 3 different web app tests.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9htV3c5tVEI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Brainf**k and C on M2 MacBook. One of them is faster \ud83e\udd14", "Time Created": null, "Time Published": "2022-09-08T11:41:43Z", "Duration": null, "Description": "Testing the M2 MacBook Air in base model and upgraded model against the M1 MacBook Air and the M1 Pro MacBook Pro, in a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QL9R-e7RUD8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is it worth it getting a M2 MacBook Pro? \ud83e\udd14", "Time Created": null, "Time Published": "2022-07-07T15:59:19Z", "Duration": null, "Description": "Here are my thoughts about the #M2MacBookPro for #developers and whether they should be running out to buy one or waiting.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "i_O8r1YQJVo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Max vs Intel Core i9 Python Race | XPS 15 2022", "Time Created": null, "Time Published": "2022-06-29T14:53:25Z", "Duration": null, "Description": "Apple M1 Max MacBook Pro vs Dell XPS 15 with Intel Core i9 12900KF in a Python implementation of the Mandlebrot algorithm.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "osK1UhNrvZQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air after a week | PROBLEMS? What problems?", "Time Created": null, "Time Published": "2022-08-02T13:29:17Z", "Duration": null, "Description": "I made the M2 MacBook Air my daily driver for software development. This is my one week report. Don't fall into the FUD trap.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "JnErJdr8gH0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac Studio - too much for software developers?", "Time Created": null, "Time Published": "2022-03-23T20:45:21Z", "Duration": null, "Description": "Is the the Mac Studio with the M1 Ultra chip too much computer for programmers and developers? My current dock: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "r9rIaa0I61U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Tensorflow benchmark | M1 Pro vs M1 Max", "Time Created": null, "Time Published": "2022-01-04T14:30:08Z", "Duration": null, "Description": "Testing ai (tensorflow) benchmark on a M1 Pro MacBook pro vs a M1 Max MacBook pro. Grab Parallels for yourself: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Oiq4dZbXVWA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "you'll always be inferior", "Time Created": null, "Time Published": "2022-07-19T15:20:40Z", "Duration": null, "Description": "I'm reading \"Courage to be Disliked\" by Fumitake Koga and Ichiro Kishimi and here's what I got from the book as it relates to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cteeUwqjebI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel does it again, this time with Docker.", "Time Created": null, "Time Published": "2022-08-16T18:30:25Z", "Duration": null, "Description": "So far it's been pretty close between the M1 Max MacBook Pro and the 2022 Dell XPS 15 with an Intel Core i9 12900KF (Alder ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "He8JMyHRbBw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Did Docker LIE about Apple Silicon support?", "Time Created": null, "Time Published": "2021-12-09T15:00:09Z", "Duration": null, "Description": "Here is what is NOW supported by Docker on Apple Silicon. Upgrading Docker Desktop on M1 Max, M1 Pro, and the good old M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4ms32abv8lU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Sorry Apple fan boys and girls \ud83d\ude2d Intel SMASHES this one", "Time Created": null, "Time Published": "2022-07-15T11:00:02Z", "Duration": null, "Description": "So far it's been pretty close between the M1 Max MacBook Pro and the 2022 Dell XPS 15 with an Intel Core i9 12900KF (Alder ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "A2SDt-RGBZo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is Flutter KILLING the M1 SSD?", "Time Created": null, "Time Published": "2021-06-24T13:42:19Z", "Duration": null, "Description": "How well will the M1 MacBook SSD do with Flutter? We've heard a lot about the SSD issues on the M1 Macs, then to find out that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "XWdsm37raQ0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "HUGE javascript build | m1 pro/max macbooks compared", "Time Created": null, "Time Published": "2022-02-10T15:13:28Z", "Duration": null, "Description": "Benchmark of a large JavaScript project with 27000 components in Nx monorepo workspace built on M1 MacBook air, M1 Pro ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "kKCxR_2IE6M", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air vs 2015 MacBook Pro Xcode Build Test", "Time Created": null, "Time Published": "2021-01-20T19:46:15Z", "Duration": null, "Description": "In this video, I run a pretty large sized Xcode benchmark project with lots of dependencies on the new M1 MacBook Air. As many ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "q2q0-kXnTKE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Which Linus uses the M2 MacBook Air?", "Time Created": null, "Time Published": "2022-08-03T14:55:42Z", "Duration": null, "Description": "Pop quiz! Which of these Linuses uses an M2 MacBook Air (for developing the Linux kernel - oops). Get CPU/GPU temperatures ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Mw2of0OEJJ8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "My Parallels 17 first impressions | Windows 11 on a Mac", "Time Created": null, "Time Published": "2021-09-02T14:15:09Z", "Duration": null, "Description": "Parallels 17 is out now and it runs on the M1 MacBooks natively. I try Windows 11 for ARM on it to see if the advertised ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cAQzrj02et4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "is Apple Silicon ready, and does it arm?", "Time Created": null, "Time Published": "2021-07-20T13:17:12Z", "Duration": null, "Description": "There are two tools that track the readiness of Apple Silicon and software vendors' support for it. doesitarm.com and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "kyZA6ZBnoP0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "FINALLY, where the M1 Ultra REALLY shines!", "Time Created": null, "Time Published": "2022-05-17T14:50:24Z", "Duration": null, "Description": "Nerding out with SINGLE and MULTI core C++ tests on the Mac Studio with M1 Ultra, and throwing in a comparison to the M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "HoPgQKTdnxM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra vs M1 Max | Android Tests", "Time Created": null, "Time Published": "2022-04-12T15:08:33Z", "Duration": null, "Description": "Comparing the Mac Studio with M1 Ultra to MacBook Pro with M1 Max and an Intel MacBook Pro. Machine used here: Apple Mac ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-GRy3qD8Hc8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air Pre-Order is Official!", "Time Created": null, "Time Published": "2022-07-06T19:22:39Z", "Duration": null, "Description": "MacBook Air M2 now has a date, with me. #macbookair #apple #m2.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "75YiExAgoZ4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple CANCELS iMac", "Time Created": null, "Time Published": "2022-03-11T01:50:31Z", "Duration": null, "Description": "With Mac Studio here, it looks like we can say goodbye to a beloved 27\" iMac for good. Is this a good thing? The monitors that I ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ub2Osa77Cv0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple's messed up - YOU WIN!", "Time Created": null, "Time Published": "2022-05-03T14:48:15Z", "Duration": null, "Description": "Out of all the laptops that Apple released since it introduced Apple Silicon with the M1 chips in 2020, this one is the highlight, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QlqqAm9sTJg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra vs M1 Max | Xcode Tests", "Time Created": null, "Time Published": "2022-04-04T17:01:27Z", "Duration": null, "Description": "Comparing the new Mac Studio with the M1 Ultra to the MacBook Pro with M1 Max and Intel chips. In this video I use three ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "iwcVlnDx0i8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro vs M1 Max | Xcode Build Test", "Time Created": null, "Time Published": "2021-10-29T20:00:17Z", "Duration": null, "Description": "In this video, I continue to test the M1 Pro and M1 Max chips in the new MacBooks, this time with a pretty large sized Xcode project ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "HHr-R3jjafo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Does Linux run Android Studio FASTER than Windows?", "Time Created": null, "Time Published": "2021-09-09T15:10:10Z", "Duration": null, "Description": "How much faster is running Android Studio on Linux (Ubuntu) than Windows? I do several tests of Hello World app to get a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GcrNyruPIpA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 iOS Development Setup and Simulator performance Test | Intel Core i9 Comparison", "Time Created": null, "Time Published": "2020-12-22T15:35:20Z", "Duration": null, "Description": "This video shows off some native Apple software at work on the new M1 MacBook Air as compared to the Intel Core i9 16\" ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vKBuwsEEsns", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 vs M1 Pro MacBook for Flutter, React Native, NativeScript", "Time Created": null, "Time Published": "2021-11-19T15:00:24Z", "Duration": null, "Description": "M1 MacBook Air going up against M1 Pro MacBook Pro, with a getting started test for NativeScript, React Native, and Flutter.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "SnGQvD5k_cU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is switching to M1 a good IDEA? \ud83d\ude1b | Depends which M1 (Pro/Max)", "Time Created": null, "Time Published": "2021-12-01T16:18:55Z", "Duration": null, "Description": "Comparing IntelliJ IDEA usability and speed with a Java project on Intel Core i9 MacBook Pro, M1 MacBook Air, M1 Pro and M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8yJ2kmqECsU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro vs M1 Max iOS Simulator Performance", "Time Created": null, "Time Published": "2021-11-06T18:23:04Z", "Duration": null, "Description": "Native Apple software at work on the new M1 Pro vs M1 Max MacBooks testing the iOS build and simulator startup speed.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "jSHPsxW0m8g", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro MacBook Pro vs M1 MacBook Air | WEB APPS GO!!! \ud83d\ude80\ud83d\ude80", "Time Created": null, "Time Published": "2021-10-28T13:14:00Z", "Duration": null, "Description": "Testing the MacBook Pro M1 Pro (8 core 32Gb) against the MacBook Air M1 (8 core 16Gb) in a Chrome and Safari to see the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yiPbIzGgpPs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Max vs Intel Core i9 Docker Race \ud83c\udfc1 | XPS 15 2022", "Time Created": null, "Time Published": "2022-07-05T17:08:21Z", "Duration": null, "Description": "This is a test of M1 Max MacBook Pro vs a Dell XPS 15 with an Intel Core i9, and how quickly they each build a Docker(ized) app.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "WcT0IBHF5nE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "i tried programming on the CHEAPEST laptop", "Time Created": null, "Time Published": "2022-05-24T18:37:18Z", "Duration": null, "Description": "I wanted to see what the developer experience would be like on a really cheap laptop - is it even possible? Cheap laptop that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "H06R4tXXWZ0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i9 MacBook Python Test", "Time Created": null, "Time Published": "2021-05-20T14:00:04Z", "Duration": null, "Description": "Apple M1 MacBook vs Intel i9 MacBook in a Python implementation of the Mandlebrot algorithm. This shows off the code running ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pZAosPIcCoU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Mac vs Intel Building WebKit Multiple Times - HOW IS THIS POSSIBLE?", "Time Created": null, "Time Published": "2021-02-01T15:00:18Z", "Duration": null, "Description": "You've joined me for a number of developer build tests on the Apple M1 Mac here, but no tests have run for an extended period of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "B9C_cv8R_7U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Visual Studio 2022 for ARM is a BANGER! | On M1 Max MacBook Pro", "Time Created": null, "Time Published": "2022-07-01T18:06:50Z", "Duration": null, "Description": "It's here. Visual Studio 2022 for ARM is in preview to get ready for Microsoft's own ARM developer hardware that's slated for end of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "viRMHT6T6fo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air vs Intel i9 MacBook Pro Sorting 1000000 Items", "Time Created": null, "Time Published": "2021-03-04T16:48:30Z", "Duration": null, "Description": "In this video, I continue to test the new Apple M1 MacBook Air, this time with a low level Quick sort test written in C++ and built on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9gi8vhlGezQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "One of these M2 Airs is $1000 CHEAPER. Can I tell which one?", "Time Created": null, "Time Published": "2022-08-18T11:30:04Z", "Duration": null, "Description": "Is the M2 MacBook Air that costs $1000 more really worth it? I put them to a real world workflow test based on a commenter's ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "iPftvzviHwE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Unexpected results \ud83d\ude15 ML @TensorFlow tests on M1 Pro/Max MacBooks", "Time Created": null, "Time Published": "2021-12-02T17:24:40Z", "Duration": null, "Description": "Testing a ML benchmark with TensorFlow on a M1 Pro MacBook vs M1 Max MacBook, and got some unexpected results at the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PxM3w0qjelc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Programming on a gaming laptop", "Time Created": null, "Time Published": "2022-02-17T19:26:49Z", "Duration": null, "Description": "Here's what I look for when programming on a gaming laptop. \u25b6\ufe0fMy recent tests of M1 Pro/Max MacBooks for Developers ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "JJ7MEsbbyDI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "5 MacBooks BATTERY strained and drained | Software Developer test", "Time Created": null, "Time Published": "2021-11-16T14:30:06Z", "Duration": null, "Description": "How long until one of these 5 laptops dies while compiling a large code base? Get TG Pro (temperature readout and fan control) ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "XNyeNsCkrUo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "GoLang Surprise \ud83d\ude2e M1 (pro/max) vs Intel MacBooks", "Time Created": null, "Time Published": "2022-01-25T15:25:56Z", "Duration": null, "Description": "Which of these machines will build and run a Go benchmark fasterest? Intel MacBook Pro, M1 MacBook Air, M1 Pro and M1 Max ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PyE3U3rRR14", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Sorry M1, time to take a bow | M1 vs M1 Pro 8 Core test", "Time Created": null, "Time Published": "2021-11-10T15:32:38Z", "Duration": null, "Description": "You've all asked for it, well here is the test of the low end MacBook Pro with M1 Pro going up against the M1 MacBook Air.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QLpUMgCrRQs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Did we lose screen space in 2021 16" MacBook Pro?", "Time Created": null, "Time Published": "2021-10-30T18:35:39Z", "Duration": null, "Description": "Is the new 2021 16\" MacBook Pro actually smaller and can fit less code than the previous design without the notch? \u25b6\ufe0f M1 Pro ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7dlNOke_gik", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook with Parallels Running Visual Studio Projects", "Time Created": null, "Time Published": "2021-01-25T15:00:08Z", "Duration": null, "Description": "There is a new build of Parallels preview out for the ARM architecture that runs on the M1 MacBooks. I got it installed and running ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BY-O2i365BQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is Android faster on the M1 Max than on M1 Pro MacBook?", "Time Created": null, "Time Published": "2021-11-15T15:49:58Z", "Duration": null, "Description": "This is a race! Is the M1 Max MacBook going to beat the M1 Pro MacBook in this Android Build test? Related videos: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FZ4a9-QfipM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "\u2705 C++ single and multi core race | M1/M1 Pro/M1 Max", "Time Created": null, "Time Published": "2021-12-16T16:36:44Z", "Duration": null, "Description": "Testing single and multi core performance on the M1 MacBook Air vs M1 Pro and M1 Max MacBook Pros. \u25b6\ufe0f Intel MacBook ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DvfgKqdakRc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Which is best for Unity? M1, M1 Pro, or M1 Max?", "Time Created": null, "Time Published": "2021-11-23T15:07:32Z", "Duration": null, "Description": "Using Unity, building projects, and gameplay on the M1 MacBook Air vs M1 Pro MacBook Pro vs M1 Max MacBook Pro. Help out ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "SavknSEj930", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "had to find out for myself", "Time Created": null, "Time Published": "2022-08-25T12:30:13Z", "Duration": null, "Description": "dotnet, or .NET runs natively on Apple Silicon now, and for a video about that, you can see this: https://youtu.be/pKCrZEzuALA But ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "HoR36iHjQ94", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Why is this still around? | M2 vs M1 MacBook Air", "Time Created": null, "Time Published": "2022-07-08T20:08:28Z", "Duration": null, "Description": "The M2 MacBook Air went on sale today, but why is M1 MacBook Air still a thing? #macbookair #m2macbookair #m1 #m2.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "s4p_ngaJVwY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is the upgrade worth it? | Windows on Mac via Parallels 17", "Time Created": null, "Time Published": "2021-08-26T16:34:24Z", "Duration": null, "Description": "Parallels 17 is out now and it runs on the M1 MacBooks natively. I take it out for a spin to see if there are improvements Use my ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZjCAvBKbGPM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air vs Intel MacBook Pro - React Native Performance", "Time Created": null, "Time Published": "2021-01-27T17:50:15Z", "Duration": null, "Description": "In this video, I continue to test the new Apple M1 MacBook Air vs my Intel Core i9 16\" MacBook Pro (64GB, i9-9980HK CPU ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "N7wzU3TlmcE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Thinking about running Docker on M2?", "Time Created": null, "Time Published": "2022-10-05T13:32:36Z", "Duration": null, "Description": "Testing Docker on M2 and M1 Pro MacBooks. \u25b6\ufe0f Docker on Apple Silicon Playlist: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xL76mKHfGa8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple: Sorry, we don't want your Intel MacBook \ud83d\ude14", "Time Created": null, "Time Published": "2022-09-07T13:35:13Z", "Duration": null, "Description": "Apple MacBooks have a high resale and trade-in value. But since Apple Silicon MacBooks came out, Intel MacBooks seem to get ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Jjcri3vYods", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Macs STILL don't run these dev tools natively", "Time Created": null, "Time Published": "2021-07-13T13:30:03Z", "Duration": null, "Description": "The M1 Macs can do some amazing things, but not all software is supported on it yet. Here are some popular developer tools that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xQgYhNnuQBU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac guy forced to buy Windows laptop for software dev", "Time Created": null, "Time Published": "2022-05-19T14:48:33Z", "Duration": null, "Description": "I love my MacBook Pro, but I HAVE to get a Windows/Linux laptop for software development. Here are the things I look for in a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "EyCRcGrpMYs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro/Max Power Modes TESTED | Should you keep it plugged in?", "Time Created": null, "Time Published": "2021-11-09T18:52:15Z", "Duration": null, "Description": "Comparing power modes and how they effect M1 Pro and M1 Max MacBook Pros as well as the Intel Core i9 for good measure.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "RD6qELOBr5U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 vs Intel i9 JavaScript Nx Workspace Install and Build Speed Comparisons", "Time Created": null, "Time Published": "2020-12-14T15:00:07Z", "Duration": null, "Description": "Continuing this series of exploring the new Apple M1 Macs for software developers, I compare the MacBook Pro 16\" with Core i9, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "3b8ttI5SHos", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Beginner on M1 Max MacBook VS. Pro on Chromebook - Web Developer Showdown!", "Time Created": null, "Time Published": "2022-07-21T16:32:31Z", "Duration": null, "Description": "Luke Barousse and do a web dev challenge to see how much a better machine matters in programming. Subscribe to Luke here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "63_lB0mB6O0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Does Intel i9 beat the M1 in Android Studio build?", "Time Created": null, "Time Published": "2021-08-19T16:39:20Z", "Duration": null, "Description": "How much faster will running Android Studio with Apple Silicon support be compared to running the same large app build on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Tz0TCWUdlbs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel wipes the floor again | Sorry M1 Max", "Time Created": null, "Time Published": "2022-07-18T12:00:26Z", "Duration": null, "Description": "So far it's been pretty close between the M1 Max MacBook Pro and the 2022 Dell XPS 15 with an Intel Core i9 12900KF (Alder ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pxQ22vXED5s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Fastest Android Emulator yet | M1 MacBook test", "Time Created": null, "Time Published": "2021-08-13T14:02:51Z", "Duration": null, "Description": "The Android Emulator is finally supported on Apple Silicon natively and I'm testing it out on my M1 MacBook Air. I also compare it ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "fArLErtffLY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mobile Developer Tries Svelte Native for the First Time", "Time Created": null, "Time Published": "2020-11-20T14:05:06Z", "Duration": null, "Description": "Never touched Svelte at all yet, but I hear good things. Svelte Native is the mobile (anti) framework that renders native iOS and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QSPFx9R99-o", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Does Ryzen 9 beat the M1 in Android Studio build?", "Time Created": null, "Time Published": "2021-08-19T16:39:18Z", "Duration": null, "Description": "How much faster will running Android Studio with Apple Silicon support be compared to running the same large app build on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "N6e8NUNHFWo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Docker on M1 Pro and M1 Max | against M1 and Intel", "Time Created": null, "Time Published": "2021-11-05T13:08:21Z", "Duration": null, "Description": "Testing Docker on M1 Max, M1 Pro, Intel Core i9 MacBook Pros and the good old M1 MacBook Air. CPU temperatures and fan ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "1IQdSHNmoIo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is the Apple Silicon version of Unity faster? And by how much?", "Time Created": null, "Time Published": "2021-07-22T13:00:00Z", "Duration": null, "Description": "Unity alpha channel now supports Apple Silicon. In this video I test the Apple Silicon version against the x64 version in a build and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GfDMoDqAJSk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Macs and VSCode Universal", "Time Created": null, "Time Published": "2021-03-12T15:37:02Z", "Duration": null, "Description": "Taking another look at VSCode, this time VSCode Universal and how it runs on the M1 Mac. We're also looking at actually ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "sWav0WuNMNs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Docker on M1 MacBook vs Ryzen 7 Lenovo", "Time Created": null, "Time Published": "2021-06-11T13:19:49Z", "Duration": null, "Description": "In this video I test the M1 MacBook Air vs Ryzen 7 Lenovo ThinkBook in a Docker test as I deploy a container and run a Node ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "zhXsMlv_4Ik", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Macbook vs Intel EVO Ideapad for Android Development?", "Time Created": null, "Time Published": "2021-03-26T14:26:49Z", "Duration": null, "Description": "In this video I test the Lenovo IdeaPad Slim 9 with an Intel i7 11th Generation processor. I build an Android benchmark project ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mCu9iDweorM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Air: M2 vs M1 vs Intel", "Time Created": null, "Time Published": "2022-07-26T14:15:37Z", "Duration": null, "Description": "The M2 MacBook Air has no fans, which means it will throttle (slow down) the processor when the temperature gets too high.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "w6HPKk8lkDQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra any good for Unity? | vs RTX3080", "Time Created": null, "Time Published": "2022-04-07T20:03:02Z", "Duration": null, "Description": "Using Unity, building projects, and gameplay on the M1 Ultra Mac Studio vs a PC with Intel Core i9 12900KF and NVIDIA ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8JwFkmqvRMA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 and VSCode Performance", "Time Created": null, "Time Published": "2020-12-16T15:00:08Z", "Duration": null, "Description": "Here we are again exploring the new Apple M1 Macs for software developers. In this video let's take a look at how (poorly?) Visual ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "o4diDh7f2Dk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra is fast, but is Intel 12th Gen faster?", "Time Created": null, "Time Published": "2022-03-27T20:02:06Z", "Duration": null, "Description": "Testing the Mac Studio M1 Ultra against the Intel Core i9 (12900KF) in Chrome to see web test scores in 3 different web app tests.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xzV8zqByBm0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Loudest MacBook Fans Found | M1 Max and M1 Pro", "Time Created": null, "Time Published": "2021-10-31T19:18:52Z", "Duration": null, "Description": "In this video I test the sound of the MacBook Pro fans on the new M1 Pro and M1 Max MacBook Pros as well as the Intel Core i9 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "r9rIaa0I61U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Tensorflow benchmark | M1 Pro vs M1 Max", "Time Created": null, "Time Published": "2022-01-04T14:30:08Z", "Duration": null, "Description": "Testing ai (tensorflow) benchmark on a M1 Pro MacBook pro vs a M1 Max MacBook pro. Grab Parallels for yourself: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "MtVAUWHBdnc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Stack Overflow - Is this the END?", "Time Created": null, "Time Published": "2021-06-04T21:33:49Z", "Duration": null, "Description": "Is Stack Overflow destined doomed now that it's been acquired by a big fish investing company?", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Zun4ulyvxGw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is M1 Ultra twice faster than Intel 12900FK? Well, here's the thing...", "Time Created": null, "Time Published": "2022-03-31T17:27:56Z", "Duration": null, "Description": "There are many coding benchmark videos out there about the Mac Studio and the M1 Ultra, and they are heavily borrowing from ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tnqLWQzVZBk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air and Intel i9 MacBook Pro REAL JavaScript Project Build Speed Shootout", "Time Created": null, "Time Published": "2020-12-21T15:00:32Z", "Duration": null, "Description": "We'll keep rolling with this series covering the performance of the new Apple M1 Macs for software developers vs my MacBook ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pKCrZEzuALA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Which .NET on a Mac type are you?", "Time Created": null, "Time Published": "2022-01-27T13:22:55Z", "Duration": null, "Description": "dotnet, or .NET as it's been known from time to time, has grown into a nice cross platform framework that even runs natively on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NxcumAU5kHs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air vs M1 vs M1 Pro", "Time Created": null, "Time Published": "2022-09-06T16:17:10Z", "Duration": null, "Description": "M2 MacBook Air in two configurations compared to the M1 Pro MacBook Pro and the M1 MacBook Air in Python single core and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BPtHVjBznZE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air vs Dell XPS with Intel i7 EVO and Android Development Performance", "Time Created": null, "Time Published": "2021-02-09T14:55:03Z", "Duration": null, "Description": "Admittedly it's still a bit early for Android development on the new M1 Macs, but so many of you asked to see Android build tests ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "E9vyQvJE060", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "one of these M2 MacBook Airs is not like the other", "Time Created": null, "Time Published": "2022-07-28T23:07:42Z", "Duration": null, "Description": "Which is which? Bet you can't even tell. #m2 #macbookair #macbookair2022.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DO39o5lQanQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air Good for Unity?", "Time Created": null, "Time Published": "2022-09-16T11:32:16Z", "Duration": null, "Description": "Using Unity, building projects, and gameplay on the M2 MacBook Air vs the M1 Pro MacBook Pro. Help out this channel and use ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AiDjFd6M3rA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Where is Parallels' FREE version? | M1 Pro/Max and virtual machines", "Time Created": null, "Time Published": "2021-11-11T19:36:44Z", "Duration": null, "Description": "Parallels, VirtualBox, UTM, VMWare, etc. Who supports M1 (Apple Silicon in general), who is working on it, and who doesn't care.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8n2A_ztNTrU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I made Python 2x FASTER on my M1 MacBook", "Time Created": null, "Time Published": "2021-08-31T13:37:28Z", "Duration": null, "Description": "In this video I run single and multi core Python tests on the M1 MacBook Air (16GB model). Comparing the Apple Silicon vs Intel ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "WZR0nzAsYGw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "dotnet 6 is HOW MUCH FASTER?! | Apple M1 Max vs .NET 5 on Intel", "Time Created": null, "Time Published": "2021-11-24T15:08:33Z", "Duration": null, "Description": "dotnet 6 is finally out and with ARM support. I'm testing my code on dotnet 5 on an x64 Intel Core i9 machine and comparing the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "o9GtzlVwgVI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Epic vs Apple and the future for App Developers", "Time Created": null, "Time Published": "2021-09-13T19:55:55Z", "Duration": null, "Description": "How does the Epic vs Apple ruling affect developers and really anyone who publishes apps to the Apple App Store to make sales ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "OZcTmDhjjHk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 \ud83c\udfc6 Web App CHAMPION?", "Time Created": null, "Time Published": "2022-07-12T13:00:40Z", "Duration": null, "Description": "Let's test out web app speeds on the M1 MacBook vs M1 Max MacBook vs M2 MacBook. Going beyond the basic Speedometer ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vx5GlT2HyFE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "FFmpeg race \ud83c\udfc1  | M1 Max/Ultra  \ud83c\udd9a Intel Core i9 12th Gen |", "Time Created": null, "Time Published": "2022-06-17T18:15:03Z", "Duration": null, "Description": "Testing ffmpeg on the M1 Max MacBook Pro vs the Dell XPS 15 with a 12th Gen Intel Core i9 chip, and throwing in the M1 Ultra ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "b856uZyEFhQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "should have gotten this sooner", "Time Created": null, "Time Published": "2022-08-31T13:30:09Z", "Duration": null, "Description": "This is the best thing I've tried to boost my productivity when I'm on the go. \u25bbGet the ROADOM monitor here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "u10Gzb7YiiM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air \ud83d\udd25 crazy prices and wait times \ud83e\udd14", "Time Created": null, "Time Published": "2022-07-12T08:00:17Z", "Duration": null, "Description": "Apple revealed a new #MacBookAir with the #M2 processor and an all-new design during its Worldwide Developer Conference ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "jV54BoR9JBU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "HUGE Xcode build on M1 Pro and M1 Max - who will win?", "Time Created": null, "Time Published": "2021-11-04T13:30:06Z", "Duration": null, "Description": "How long do M1 Pro and M1 Max take to build this HUGE Xcode project? A real code base built from command line using Xcode, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QXEvTP0IVNU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "What you GIVE UP if you DON'T get the M2 MacBook Air", "Time Created": null, "Time Published": "2022-09-13T12:30:08Z", "Duration": null, "Description": "Here's a list of things you'll give up if you don't get the M2 MacBook Air, and decide to buy the M1 MacBook Air instead.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7-N62bgsxMI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra vital signs", "Time Created": null, "Time Published": "2022-03-25T20:56:03Z", "Duration": null, "Description": "Taking some vitals of the new Apple Mac Studio with the M1 Ultra chip while stressing it out a bit to see how it can stand up to the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6qytTPTyDtI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel Node Stress Test", "Time Created": null, "Time Published": "2021-01-13T15:11:20Z", "Duration": null, "Description": "Let's keep going with this series covering the performance of the new Apple M1 Macs for software developers vs my MacBook Pro ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "imGpNsfJ8rM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M2 MacBook Air stand up to MacBook Pro", "Time Created": null, "Time Published": "2022-09-27T15:23:11Z", "Duration": null, "Description": "Parallels 18 (not sponsored) lets us run Visual Studio for ARM in Windows on a Mac. Here are the performance differences ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tf4gRH_tEv8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Android Studio on Apple Silicon is HOW FAST?", "Time Created": null, "Time Published": "2021-08-11T13:18:39Z", "Duration": null, "Description": "How much faster will running Android Studio with Apple Silicon support be compared to running the same large app build on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "YjUCXGGJu7E", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 and Android Emulator", "Time Created": null, "Time Published": "2020-12-24T12:35:32Z", "Duration": null, "Description": "The Android emulator now works on the Apple M1 chip (Apple Silicon), but only in preview mode. This means that not all ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "R2KkJ_Zawnk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I had no idea you could do this - MacOS using React?", "Time Created": null, "Time Published": "2022-03-11T18:37:28Z", "Duration": null, "Description": "Jim Nielsen's blog post: https://blog.jim-nielsen.com/2022/inspecting-web-views-in-macos NativeScript training courses ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "5ZxCxW9t1ss", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook JavaScript Setup", "Time Created": null, "Time Published": "2020-12-11T12:19:12Z", "Duration": null, "Description": "In this series of exploring the new Apple M1 Macs for us, software developers , I'll kick things off by setting up a simple ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pDzNK7iudgI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 Ultra Benchmarks vs Intel 12th gen | Geekbench 5", "Time Created": null, "Time Published": "2022-03-09T17:50:39Z", "Duration": null, "Description": "Apple's peek event just ended where the new M1 Ultra chip and Mac Studio were revealed, AND the first benchmarks for the M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-vEOVHuK08c", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 vs Intel i9 SwiftUI Build Test", "Time Created": null, "Time Published": "2021-04-09T14:00:01Z", "Duration": null, "Description": "Continuing the M1 vs Intel series, this time with a SwiftUI project provided by Apple. This shows off some native Apple software at ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "0NsUUca-m74", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Flutter vs React Native vs NativeScript Startup Speeds on the M1 Mac", "Time Created": null, "Time Published": "2021-05-14T15:25:53Z", "Duration": null, "Description": "Flutter vs React Native vs NativeScript on a M1 mac in a getting started test - this includes creating a new app, building, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qWsQiOIDtEA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i7 Dell XPS 13 in a .NET Build Shootout", "Time Created": null, "Time Published": "2021-02-12T19:09:03Z", "Duration": null, "Description": "In this video I take another look at .NET performance on the Apple Silicon M1 and compare it to a Dell XPS 13 with a Code i7 11th ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "XxJtjoDhV6o", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your JavaScript sort is kinda slow", "Time Created": null, "Time Published": "2021-10-05T13:14:50Z", "Duration": null, "Description": "JavaScript's built-in sort function is SLOW! Here are 3 ways to sort numbers, some of which will be much faster, depending on the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "p8p3wWNPfQY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Xcode optimizations a WASTE of TIME?", "Time Created": null, "Time Published": "2022-05-06T15:05:42Z", "Duration": null, "Description": "After some Xcode tests comparing M1 Ultra Mac Studio with M1 Max, some of you suggested how to improve Xcode performance.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "L4NbHk5f2Bs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Could the Ryzen 9 beat the M1 Mac | Unity build speed", "Time Created": null, "Time Published": "2021-08-05T15:59:31Z", "Duration": null, "Description": "Building a Unity project on the M1 MacBook Air vs the Ryzen 9 Asus G15. M1 MacBook Air (16Gb model, 1TB SSD) as compared ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "we6QxdvkYsI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Asus ROG Laptop for Developers? + $1000 Subscriber giveaway", "Time Created": null, "Time Published": "2021-07-12T13:45:11Z", "Duration": null, "Description": "I'll be testing the Asus ROG Strix G15 laptop for developer tasks. It has a Ryzen 9 5900HX processor and a Nvidia RTX 3070 GPU ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TeJhVT9J_yc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac Studio crazy wait times", "Time Created": null, "Time Published": "2022-03-17T18:54:04Z", "Duration": null, "Description": "Didn't order one yet? This is gonna be a long wait for the Mac Studio. #macstudio #m1 #m1ultra #m1max.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "YpDVk-2SP3Y", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "WSL on Windows for ARM hosted on Apple Silicon", "Time Created": null, "Time Published": "2022-08-23T11:30:08Z", "Duration": null, "Description": "Trying to get WSL on a Windows 11 for ARM virtual machine hosted on Apple Silicon. Get Parallels here: US ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Ux0u6kzZ3j0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i9 MacBook Ruby Benchmark Test", "Time Created": null, "Time Published": "2021-06-09T14:00:20Z", "Duration": null, "Description": "Apple M1 MacBook vs Intel i9 MacBook in a Ruby implementation of the Mandlebrot algorithm. This shows off the code running on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "2I835GG8u7c", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Node Side by Side Performance Test", "Time Created": null, "Time Published": "2021-02-25T14:51:00Z", "Duration": null, "Description": "In this video, I'm doing a side by side TypeScript build test of Node for ARM and Node for x86 running via Rosetta on the new M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9htV3c5tVEI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Brainf**k and C on M2 MacBook. One of them is faster \ud83e\udd14", "Time Created": null, "Time Published": "2022-09-08T11:41:43Z", "Duration": null, "Description": "Testing the M2 MacBook Air in base model and upgraded model against the M1 MacBook Air and the M1 Pro MacBook Pro, in a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "bH1MV1U3I28", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook Air Running Visual Studio and Xamarin for Mac", "Time Created": null, "Time Published": "2021-01-15T17:24:02Z", "Duration": null, "Description": "In this video I continue to test the new Apple M1 MacBook and compare it to the Intel Core i9 16\" MacBook Pro (64GB, i9-9980HK ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DZEJy4uSWws", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "7 Things to Know When Learning NativeScript", "Time Created": null, "Time Published": "2019-10-28T15:13:25Z", "Duration": null, "Description": "Are you learning NativeScript? Here are the 7 things you should know. These are just my opinion. If you have something else to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "e4wCHtgdKgI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Max can't be stopped! | More monitor tests to slow it down", "Time Created": null, "Time Published": "2022-01-11T14:30:19Z", "Duration": null, "Description": "You had some ideas on how I could slow down my MacBook Pro with the M1 Max. In this video I run some of your suggestions.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "LM47upb4170", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "it's ugly, but I picked it anyway", "Time Created": null, "Time Published": "2022-02-15T20:54:56Z", "Duration": null, "Description": "I finally decided to switch away from my iMac to the new MacBook. Surprise, surprise. Here's why I did it. \u25b6\ufe0fMy recent tests of M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "sIj2GSGu_TQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel FIGHTS back! | End of the M1?", "Time Created": null, "Time Published": "2022-01-06T14:59:26Z", "Duration": null, "Description": "Good stuff coming from Intel in 2022. Is it time to reconsider getting an M1 MacBook and instead wait a little bit for the new PC ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "3O-rsAFw8J8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Windows Setup - Step by Step", "Time Created": null, "Time Published": "2018-12-31T20:23:35Z", "Duration": null, "Description": "In this tutorial, I show you how to setup a NativeScript development environment from scratch, on a new Windows laptop.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ULuN3E_D8F0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "The 8 Bad Habits of a NativeScript Developer", "Time Created": null, "Time Published": "2019-12-12T10:00:05Z", "Duration": null, "Description": "I share my experience with some bad habits that NativeScript developers have, including me sometimes. Platform Specific ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "c7PEuIKGGiY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Force Component Destroy by Using Page Life Cycle in NativeScript Angular Tutorial", "Time Created": null, "Time Published": "2019-05-01T12:34:23Z", "Duration": null, "Description": "NativeScript Angular keeps navigated components alive on a stack. This is great for performance, since the framework doesn't ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ntSiq7cEzpw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "i screwed up - bought m1 max macbook", "Time Created": null, "Time Published": "2022-03-18T14:10:54Z", "Duration": null, "Description": "I bought the M1 Max MacBook Pro, but I should have bought the Mac Studio. My current dock: https://amzn.to/3ijmNFH My latest ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "C6gGz2hTV-k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook with Parallels Faster .NET Build than PC?", "Time Created": null, "Time Published": "2021-06-03T14:43:31Z", "Duration": null, "Description": "I ran a Visual Studio 2019 build of a .NET Blazor project and it seems faster on a MacBook Pro with Parallels than on a Windows ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-HOWvvOnhHQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook - Android Studio Setup and Performance", "Time Created": null, "Time Published": "2020-12-23T14:21:35Z", "Duration": null, "Description": "In this video I'm setting up an Android development environment on the new Apple M1 MacBook Air with 16GB of RAM. Related ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BBJPrQtpAVA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Buy the Apple M1 or wait?", "Time Created": null, "Time Published": "2021-10-07T14:50:10Z", "Duration": null, "Description": "Some thoughts on the upcoming Apple M series processors, proposed specs, and other stuff. #m1 #m1x #m2 #m1 #MacBook ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rMwziErHFD4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "is software engineering hard?", "Time Created": null, "Time Published": "2021-07-02T14:00:19Z", "Duration": null, "Description": "Is software engineering hard or easy. The real answer: it's complicated. It's really easy to get started, and if you are at all interested ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "YcOVeXc8Eo4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "my hopes and dream coming true, or just meh?", "Time Created": null, "Time Published": "2022-08-10T14:52:29Z", "Duration": null, "Description": "Finally there is a reasonably affordable option for a portable monitor that works pretty well. \u25bbYou can get the monitor here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "s4PB9NnuNos", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Faster Android Build | M1 Ultra vs Intel Core i9", "Time Created": null, "Time Published": "2022-04-27T15:18:14Z", "Duration": null, "Description": "Android build speed tests on Mac Studio with M1 Ultra vs Intel 12th Gen machine. \u25b6\ufe0fMy recent tests of M1 Pro/Max MacBooks ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "3jU11l9xE6k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Why Intel MacBook BEAT M1 Max in this JavaScript test", "Time Created": null, "Time Published": "2021-12-07T16:26:45Z", "Duration": null, "Description": "Why is this JavaScript code running faster on the MacBook Pro with the Intel Core i9 chip instead of on the new MacBook Pro with ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GNQgkn-fcYA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "The right way to Docker", "Time Created": null, "Time Published": "2022-09-04T19:32:03Z", "Duration": null, "Description": "Kris Rivera is my guest today to help me Dockerize my app. This app has an Angular front end and an Node with Express ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "g0sBgZ-7g3k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Sorry M1 Mac \ud83d\ude22 Ryzen 9 sorting in Python", "Time Created": null, "Time Published": "2021-09-14T14:11:09Z", "Duration": null, "Description": "Apple M1 MacBook vs Ryzen 9 in a Python race once again, this time in an extreme single core test sorting 1 billion numbers.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "fVfg58OHl1o", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I run Android Emulator FASTER | M1 vs Intel MacBook", "Time Created": null, "Time Published": "2021-08-24T14:00:12Z", "Duration": null, "Description": "The Android Emulator is finally supported on Apple Silicon natively and I'm testing it out on my M1 MacBook Air vs my 16\" ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ST6TrTCfHFk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Programming Languages RANKED", "Time Created": null, "Time Published": "2022-09-29T11:18:38Z", "Duration": null, "Description": "Visualizing programming language performance. Devices I use every day My favorite external drive (dependable): ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FoLRV7pXDtw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel MacBook BEAT M1 Max AGAIN | c++ test", "Time Created": null, "Time Published": "2021-12-14T15:41:41Z", "Duration": null, "Description": "I try to explain why the Intel Core i9 MacBook Pro runs this C++ code faster than the new M1 Max MacBook Pro and how ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tgS1P5bP7dA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 vs Ryzen 7 | JavaScript Build Test - Another Knockout", "Time Created": null, "Time Published": "2021-05-24T13:40:43Z", "Duration": null, "Description": "M1 vs Ryzen 7 JavaScript Build Test. Because I suspected the M1 MacBook Air will beat the Ryzen 7 Lenovo ThinkBook in ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mmkDyV59nRo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Setting up new M2 MacBook for my software development", "Time Created": null, "Time Published": "2022-07-11T11:02:05Z", "Duration": null, "Description": "Here I go through setting up a new M2 MacBook for software development, the way I usually set things up for my own tasks.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "b6AaKgebRjo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Why is your python sort 80x slower?", "Time Created": null, "Time Published": "2021-10-12T14:00:13Z", "Duration": null, "Description": "Python itself is pretty slow as I demonstrate here with a sort of a large data set, but has a pretty neat feature that allows you to use ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "afP5-OjpWRE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Ryzen 7 Lenovo .NET 6 Test", "Time Created": null, "Time Published": "2021-06-17T18:18:43Z", "Duration": null, "Description": "Apple M1 MacBook vs Ryzen 7 Lenovo in a C# implementation of the Mandlebrot algorithm. Machine specs are MacBook Air M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GDfN-CAoOtM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "More monitors = slower MacBooks? | M1 Max/Pro with several 4k", "Time Created": null, "Time Published": "2021-11-22T16:34:25Z", "Duration": null, "Description": "I plugged in multiple monitors, one at a time, into each of my MacBooks (M1 Max, two M1 Pro, and a M1 MacBook Air) to see how ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NXi2o0_JNqg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "returning macbook pro (m1 pro)", "Time Created": null, "Time Published": "2022-03-16T11:19:03Z", "Duration": null, "Description": "I'm returning the MacBook Pro with the M1 Pro chip - and thanks to the channel members! \u25b6\ufe0fMy recent tests of M1 Pro/Max ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "nwf928oFGCM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript with Azure Active Directory Authentication for Office 365 and Microsoft Graph Queries", "Time Created": null, "Time Published": "2016-08-19T00:52:36Z", "Duration": null, "Description": "In this video tutorial, I show you how to use the NativeScript OAuth plugin to get an access token from Azure AD that can be used ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "1PmSSpTQuaw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Max is fast, but HOW fast? | M1 Max vs Intel Core i9 MacBook Pro", "Time Created": null, "Time Published": "2021-11-01T20:29:34Z", "Duration": null, "Description": "Testing the MacBook Pro M1 Max (10 core 64Gb) against the MacBook Pro Intel Core i9 (8 core 64Gb) in a Chrome and Safari to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mnYxl7dUb2g", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Max vs M1 Pro Temperature test", "Time Created": null, "Time Published": "2021-11-07T18:21:33Z", "Duration": null, "Description": "Taking periodic temperature measurements of M1 Max MacBook Pro, vs M1 Pro, Intel Core i9, and M1 MacBook Air, while ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "1f_ahSt_UI0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "OpenCV Build SLOW? Make it faster!", "Time Created": null, "Time Published": "2021-04-16T14:00:01Z", "Duration": null, "Description": "OpenCV building slow for you? This video shows off some native builds at work on the new M1 MacBook Air (16Gb model) as ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "biGSa5x39sQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "apple bleeding ARM brains", "Time Created": null, "Time Published": "2022-02-02T15:52:53Z", "Duration": null, "Description": "Apple had some success with their transition to M1, but now their top ARM engineers are leaving. Grab Parallels for yourself: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Mp1q1SFGOKI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "DON'T get a M1 Mac for Programming | my 8 month take", "Time Created": null, "Time Published": "2021-07-29T14:00:17Z", "Duration": null, "Description": "Why wouldn't you get a M1 Mac for software development? Here are just a few reasons. #m1 #MacBook \u25b6\ufe0f M1 Macs STILL ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pNitFeYYzAo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Apps from Scratch 2020 | NativeScript Tutorial | JavaScript", "Time Created": null, "Time Published": "2020-02-11T11:00:09Z", "Duration": null, "Description": "In this NativeScript tutorial (part 1), I create a new JavaScript project using the NativeScript CLI and then delete everything so I can ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TTYSxXmpZWA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Develop mobile apps on a Chromebook, what\u2019s next?", "Time Created": null, "Time Published": "2022-10-06T13:27:20Z", "Duration": null, "Description": "I love my MacBook Pro for mobile development. But there is a new tool that should allow even the cheapest Chromebooks to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-kgNeyZNatk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Github Copilot has a HIDDEN SKILL", "Time Created": null, "Time Published": "2021-07-06T14:00:00Z", "Duration": null, "Description": "Taking Github Copilot out for a spin, which is an AI (OpenAI GPT-3) powered tool that can write code for you automatically in many ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dCbr2iFbh8o", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Android Studio setup STILL tricky on M1 Pro?", "Time Created": null, "Time Published": "2021-11-13T19:21:46Z", "Duration": null, "Description": "Let's set up Android Studio on an Apple Silicon machine! Oh is it still a bit quirky? Here I show the steps on M1 Pro MacBook.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TLj6LNm8Khw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i7 EVO Lenovo in Unity Build Comparison", "Time Created": null, "Time Published": "2021-03-19T14:00:17Z", "Duration": null, "Description": "Will the Intel EVO line of processors make a difference for them now that the M1 MacBooks have been smashing so many records ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Y3u0ffqcZLg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Increase Your Productivity as a Software Developer or Learning Programming \ud83e\udd13", "Time Created": null, "Time Published": "2022-05-31T15:53:52Z", "Duration": null, "Description": "I've been experimenting with improving my productivity as a software developer. In this video I share what I see working for me.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "k7Y9c-T8uDk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "what's causing the M1 CPU to spike?", "Time Created": null, "Time Published": "2022-04-05T19:31:46Z", "Duration": null, "Description": "Why use/not use ripgrep: https://blog.burntsushi.net/ripgrep #ripgrep #vscode NativeScript training courses ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8y9BecKDCUI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "What's New in NativeScript 7", "Time Created": null, "Time Published": "2020-09-01T19:34:17Z", "Duration": null, "Description": "In this overview video, I discuss a few of the new updates in NativeScript version 7.0. More video deep dives to come on several of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NGy8SjHFaQo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "fresh hot nand chips | M2 MacBook Air vs M1 Pro MacBook Pro SSD Speeds", "Time Created": null, "Time Published": "2022-08-02T17:56:46Z", "Duration": null, "Description": "M2 MacBook Air vs M1 Pro MacBook Pro SSD Speeds. Related videos \u25b6\ufe0f Apple M2 and Developers Playlist - my tests so far ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "U2XOLGw1xAs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is NativeScript Playground A Serious Tool?", "Time Created": null, "Time Published": "2020-11-06T18:15:01Z", "Duration": null, "Description": "Should you use the NativeScript Playground? Here are some thoughts. NativeScript training courses ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "b13WhqJPH50", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "When is .NET 6 with ARM support for M1 Pro/Max happening?", "Time Created": null, "Time Published": "2021-10-26T14:26:39Z", "Duration": null, "Description": "Well it's been a long time in the making, but we're getting close to having .NET supported on the Apple M1 machines, M1 Pro and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "bySnwt-nF-k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 vs Intel Core i9 Cross Platform Mobile App Build Speed - NativeScript", "Time Created": null, "Time Published": "2020-12-25T13:33:46Z", "Duration": null, "Description": "Back with another comparison video of the Apple M1 MacBook Air (16GB) vs an Intel Core i9 MacBook Pro (64GB, i9-9980HK ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DkxHeRcBI7U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript App Contest Winners", "Time Created": null, "Time Published": "2020-06-04T11:38:02Z", "Duration": null, "Description": "Thanks for all the submissions, and for your votes. Here are the top three winners of the NativeScript app contest.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6ad1mbqIVhU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Dear Apple, do better!", "Time Created": null, "Time Published": "2022-03-31T13:03:55Z", "Duration": null, "Description": "It's like Tim Cook himself saw my last video and made sure these ports were closer - https://youtube.com/shorts/2EkKx5orKeI.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "wlRdGPAqWl8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Run Multiple Versions of NativeScript at the SAME TIME Using NPX", "Time Created": null, "Time Published": "2019-06-08T12:12:56Z", "Duration": null, "Description": "If you have version 5.2 or higher of NPM installed, then you already have NPX - an amazing tool that executes binaries from the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ndgDaA0Vq0U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Gradient in ActionBar on iOS in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-03-18T11:00:32Z", "Duration": null, "Description": "In this NativeScript tutorial, Shiva Prasad shares a tip on how to get a gradient up in your iOS ActionBar in NativeScript. Follow ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "bZ7yF2jRUKM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "wwdc 2022 | what's coming?", "Time Created": null, "Time Published": "2022-04-06T15:56:28Z", "Duration": null, "Description": "A developer's perspective and wishlist of what to expect from the next Apple event: wwdc 2022. Apple's announcement here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "05XoA7IhTp8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Ultra vs Intel PC and Docker", "Time Created": null, "Time Published": "2022-03-30T15:32:24Z", "Duration": null, "Description": "In this video I take a look at Docker for Apple Silicon M1 Ultra. I perform a build speed test on a real project, and then on a large ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xeaCORCYmHI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How FAST is your internet?", "Time Created": null, "Time Published": "2022-09-10T14:22:19Z", "Duration": null, "Description": "Check your speed from anywhere using command line tools on Mac, Windows, and Linux. My favorite external drive: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Ad39jwkBLnk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Visual Studio 2022 on M1 Max | First Look", "Time Created": null, "Time Published": "2021-11-10T23:32:21Z", "Duration": null, "Description": "Good news, or is it? Visual Studio 2022 is out! Let's try it on a Mac. Uh oh. Use my affiliate link to grab Parallels and support my ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PPYi2PzeVAM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs 2015 MacBook Pro Node Stress Test", "Time Created": null, "Time Published": "2021-01-21T19:52:02Z", "Duration": null, "Description": "Another fun little throwback test, this time covering the performance of the new Apple M1 MacBook Air in a NodeJS Stress test, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "_HB2f7MORFo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 Pro/Max and why Intel LOST", "Time Created": null, "Time Published": "2021-10-25T17:01:36Z", "Duration": null, "Description": "Now that the Apple M1 Pro and M1 Max chips are out, let's do a quick review why Intel lost Apple as a customer, and how it ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7CXWzQMzWVA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Mac redeems itself | REAL Rust test on M1, M1 Max/Pro, Intel", "Time Created": null, "Time Published": "2022-01-18T20:07:51Z", "Duration": null, "Description": "You've been asking for a Rust test - well here we have two: a benchmark, and a real world Rust project - Deno, all tested on an ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7bUWcw-wauY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac apps I use that were thrown in for free", "Time Created": null, "Time Published": "2022-07-31T11:53:45Z", "Duration": null, "Description": "These are apps that I use ALL the time, plus a few other ones that were included for free when I got a license of Parallels to run ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "H-Lf36XZAV4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I Found the Missing JavaScript Array Function", "Time Created": null, "Time Published": "2020-05-01T17:15:00Z", "Duration": null, "Description": "I've been using the Array.prototype.includes() function, but when I recently tried in in a NativeScript project with TypeScript, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "exE1WfPvAX0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript-Vue Multiple Frames | NativeScript Tutorial Vue", "Time Created": null, "Time Published": "2019-07-26T14:32:35Z", "Duration": null, "Description": "In this NativeScript Vue JS tutorial, I show you how to use multiple nested frames in NativeScript-Vue. This is useful to separate ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "v7CNR0y7K8w", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Create NativeScript Plugins Using the New Workflow", "Time Created": null, "Time Published": "2020-09-15T16:08:35Z", "Duration": null, "Description": "In this video, I introduce the new NativeScript plugin building workflow that takes advantage of the latest official plugin seed based ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yfPEwi6muts", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Sleeping Mac Studio draws more power", "Time Created": null, "Time Published": "2022-03-22T20:01:10Z", "Duration": null, "Description": "Regulate fan and get cpu and GPU temperatures with TG Pro: https://a.paddle.com/v2/click/114/137247?link=48 (affiliate) ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "0wBL73vk5PY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Visual Debugging NativeScript Apps", "Time Created": null, "Time Published": "2016-08-31T21:28:39Z", "Duration": null, "Description": "", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "KkTtJcuR3xM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Best mice for programmers | dropping them on hard surface", "Time Created": null, "Time Published": "2021-08-18T15:17:37Z", "Duration": null, "Description": "These are the mouses (mice) I tried out - from really cheap to pricey. Yes, I also dropped them from coffee table height to see if ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pFvPVlpbuko", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M2: what we don't know and can't confirm", "Time Created": null, "Time Published": "2022-03-19T20:05:09Z", "Duration": null, "Description": "Rumors and leaks are fun. I'm not a huge fan of the way they are presented at times - especially when they are presented as facts.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6LSCQJfj6TI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "DOES IT THROTTLE? Apple M2 MacBook Air Benchmarks", "Time Created": null, "Time Published": "2022-07-13T20:27:28Z", "Duration": null, "Description": "There were theories that because of M2 MacBook Pro reaching high temps, that perhaps M2 MacBook Air would throttle. The first ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FPs2TMHwV2c", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Where are the MISSING FILES in my NativeScript Webpack Build?", "Time Created": null, "Time Published": "2020-02-20T14:34:40Z", "Duration": null, "Description": "In this quick video I demonstrate how missing files could drive you crazy and how the NativeScript webpack build could be ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "nQFRtG7mo0U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Resolving Gesture Conflicts in NativeScript", "Time Created": null, "Time Published": "2019-03-06T16:18:34Z", "Duration": null, "Description": "How do you handle multiple concurrent gestures in a NativeScript app, without the gestures conflicting? We'll take a look at how a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "zAIFdoFy1Ow", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Debug Layouts in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-05-08T11:36:30Z", "Duration": null, "Description": "In this NativeScript tutorial, Shiva Prasad shows how to use the tools you already have to debug layouts in NativeScript apps by ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "EcCVWP5_vl4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac guy thinks he has a chance: dotnet challenge", "Time Created": null, "Time Published": "2022-05-13T18:20:38Z", "Duration": null, "Description": "I've build a web application using ASP.NET Core, and now I'll add some sweet UI components to it to spruce it up. Free trial of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7wbIhgE9PX8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "THIS Mechanical Keyboard Made Me a 10X Developer (April Fools Joke)", "Time Created": null, "Time Published": "2021-04-01T13:30:30Z", "Duration": null, "Description": "The best mechanical keyboard I've ever used and one that made me a 10X Developer.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vfNIF9lF5kc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Trying out React Native for the First Time", "Time Created": null, "Time Published": "2020-12-04T14:11:03Z", "Duration": null, "Description": "So I finally did it. I tried React Native. And it didn't even hurt. A couple weeks ago I also tried out Svelte Native. Here's the video on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Fuu_Onv7buY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Event Bubbling and Gestures in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-11-18T10:00:02Z", "Duration": null, "Description": "In this NativeScript tutorial, I show a few gotchas when it comes to event bubbling and specifically nested view gesture handling.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "gmCpp9YINzM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Hacking a multi-core #webapp TEST \ud83c\udfc1", "Time Created": null, "Time Published": "2022-04-29T15:22:01Z", "Duration": null, "Description": "Speedometer tests web application speed, but only on one browser tab at a time, and thus using only one CPU core (sort of).", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Y_yPZj4WYeQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": ".NET MAUI no love for Mac users", "Time Created": null, "Time Published": "2022-04-13T19:08:25Z", "Duration": null, "Description": "what's up with dotnet Maui release candidate and not supporting iOS? #maui #dotnet #shorts.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "m-xvjDVNgrQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 vs Intel MacBooks in JavaScript Benchmark Shootout", "Time Created": null, "Time Published": "2021-04-23T15:04:24Z", "Duration": null, "Description": "I've got another M1 vs Intel video for you here. This time the M1 MacBook air goes up against the Intel Core i9 MacBook Pro in a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BTyj9r18Ln0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Mac sh*ts its pants with this Python test! (or does it? muhahaha)", "Time Created": null, "Time Published": "2021-09-07T13:00:12Z", "Duration": null, "Description": "Apple M1 MacBook vs Intel i9 MacBook in a Python race once again, this time in an extreme single core test sorting many integers ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yd3IR-BCzbI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "TOP GROWING Programming Language & how to learn it FAST", "Time Created": null, "Time Published": "2022-08-14T11:30:12Z", "Duration": null, "Description": "I wanted to learn Rust and tried a slightly different approach to learning a new programming language this time around. My current ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Ybo1qq1ZcFE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "GitHub tried to CUT ME OFF!", "Time Created": null, "Time Published": "2022-09-21T11:30:15Z", "Duration": null, "Description": "GitHub cancels my Copilot. Now what? Cheap laptop that supports dev mode: https://amzn.to/3MOeteO My current dock: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ndm9XKzIENc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Lenovo developer laptops 2022 are ... different", "Time Created": null, "Time Published": "2022-01-09T15:21:00Z", "Duration": null, "Description": "Some strange, but perhaps useful Lenovo laptops coming in 2022. Lenovo ThinkBook Plus Gen 3 - a weird monster. Lenovo ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "lNbUD6ZDdgQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Multiple Frames in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-06-14T11:29:41Z", "Duration": null, "Description": "In this video, I show you how to use multiple nested frames to separate your UI so you can navigate one part of the screen while ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yr-tTsFKrEo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook screen reflectiveness | M1 Air vs Pro #shorts", "Time Created": null, "Time Published": "2022-01-20T13:00:35Z", "Duration": null, "Description": "How reflective is the screen? #m1 #m1max #m1pro #macbook #shorts.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "hyJ2oPyaHkY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "The right way to Docker Compose \ud83d\udc33 \ud83d\udc19", "Time Created": null, "Time Published": "2022-09-12T10:42:43Z", "Duration": null, "Description": "Kris Rivera joins me again to help me Dockerize my app. This app has an Angular front end and a Node with Express backend, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "k9cxGlAlo4s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Recreating the Spotify App Artist Page in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-09-17T21:07:53Z", "Duration": null, "Description": "I always liked using the Spotify app - there's just something about it that flows well, especially the sticky, large, green play button.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "uazy0bUWj4Y", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Pod Install Command Failed Error Solution", "Time Created": null, "Time Published": "2020-01-03T19:27:47Z", "Duration": null, "Description": "Here is a quick tip for those that have recently upgraded to NativeScript 6.3 and received a mysterious error: \"pod install command ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TDEVWLHcDgM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "REACT NativeScript: First Look!", "Time Created": null, "Time Published": "2019-09-20T19:16:20Z", "Duration": null, "Description": "Well it's finally ready! After months and months of waiting, React NativeScript is the missing link that's now ripe and ready to be ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AT2GEwdJD0k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Smooth NativeScript Environment Setup on Mac", "Time Created": null, "Time Published": "2019-12-25T17:09:23Z", "Duration": null, "Description": "After a number of failures with using automatic scripts and permission issues, I've finally ran through the install on a Mac without a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "joXwqCc4JlE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Image Resize Update", "Time Created": null, "Time Published": "2020-07-10T17:22:52Z", "Duration": null, "Description": "NativeScript core modules 6.5.9 was just released with an important new feature that was created by a community member: image ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "IIX8euLFnSI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I got BANNED by Stack Overflow doing M1 Pro/Max tests", "Time Created": null, "Time Published": "2021-11-12T15:00:19Z", "Duration": null, "Description": "While doing a commenter requested test comparing the M1 with M1 Pro and M1 Max MacBooks, I got myself blocked by Stack ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xQhuV5TW7PM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "About Official NativeScript Plugins", "Time Created": null, "Time Published": "2020-11-27T12:46:29Z", "Duration": null, "Description": "Where do you find official NativeScript plugins these days? In this video I'll show you what's what. Create NativeScript Plugins ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "drhDBKAxxKk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "The Missing Page and Frame Objects in NativeScript with Angular", "Time Created": null, "Time Published": "2018-11-06T23:02:01Z", "Duration": null, "Description": "That's right, since v4 the NativeScript with Angular bootsrapping code has a new option to create a frame. You are are wondering ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "f9BI4LPmGDs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intel Core i9 12th Gen laptop BENCHMARKS | Alder Lake the new BOSS?", "Time Created": null, "Time Published": "2022-01-19T15:41:50Z", "Duration": null, "Description": "we're now getting a glimpse of the first laptop intel 12th Gen Alder Lake benchmarks showing up on Geekbench. Grab Parallels ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "B5MP6xTedtQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Debugging NativeScript Apps on An ANDROID Device", "Time Created": null, "Time Published": "2020-11-04T16:45:01Z", "Duration": null, "Description": "Let's take a look at how to set up a physical Android device for USB debugging. Then how to step through your NativeScript app ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4yIfUUbnSHI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Use NativeScript App Templates", "Time Created": null, "Time Published": "2019-08-23T15:20:26Z", "Duration": null, "Description": "Watch how fast I can create a NativeScript app using my favorite template. With these NativeScript templates, you have a starter kit ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "hWFrXN74_wQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Read Programmatic Widget Values in NativeScript", "Time Created": null, "Time Published": "2019-03-09T12:22:36Z", "Duration": null, "Description": "For this installment of #iScriptNative, Pradeep asked about reading values of dynamically created switch elements in NativeScript.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8zU_oEH5dWM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i9 in Continuous TypeScript Build Test - Dell with Intel i7 the Real Winner", "Time Created": null, "Time Published": "2021-01-11T16:14:31Z", "Duration": null, "Description": "As we keep rolling with the series about M1 for developers, there is a new contender that enters the ring: Dell XPS 13. Nope, it's ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yNb9QjhR0QI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Using ANDROID RESOURCES in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-03-05T11:00:15Z", "Duration": null, "Description": "In this NativeScript tutorial, I share how to use Android resources in your cross platform mobile apps built with NativeScript. Free ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "jl7QJV_BjJc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "New Machine Unboxing and Developer Setup", "Time Created": null, "Time Published": "2022-05-20T19:43:59Z", "Duration": null, "Description": "Come hang out and let's unbox and setup the new laptop. Agenda (we didn't get to Android studio this time, but soon) Chrome ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "objiXZ4c5bs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Vue Directive Part 2: Shadow | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-04-22T16:00:24Z", "Duration": null, "Description": "In this NativeScript-Vue tutorial, I'll show you how to create a reusable directive that we'll apply to a card UI. Here we'll create a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "S0Xm4B_UPEU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Create Large Titles with Expanding Action Bar in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-09-24T20:13:38Z", "Duration": null, "Description": "In this NativeScript tutorial, I'm going to show you 5 steps to create large expanding titles that collapse into small titles. We're using ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "KMUfRHkOtBY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Quickly Organize Your package.json File", "Time Created": null, "Time Published": "2020-10-21T15:30:03Z", "Duration": null, "Description": "NativeScript with Nx Workspaces and Xplat NEW Course: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "SeTol800wFQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Bottom Sheet in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-06-20T12:49:55Z", "Duration": null, "Description": "By popular request, in this NativeScript tutorial I create an animated bottom sheet that works on iOS and Android. I use the multiple ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "p68WkRwieKo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Get Rid of the TextField Border on Android in NativeScript", "Time Created": null, "Time Published": "2019-04-25T13:33:56Z", "Duration": null, "Description": "When you add a TextField in your NativeScript apps, by default on iOS there is no border, but on Android there is a persistent ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "XC4Z5r_z7W0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Work With Safe Areas in iOS | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-10-11T19:54:10Z", "Duration": null, "Description": "Dave Coffin (@davecoffin) shows us how to work with iOS safe areas in this NativeScript tutorial. \u25bb SHARE Share this video with ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cZjDyh6gM-I", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Asahi Linux PERFORMANCE on M2 and M1 Macs \ud83d\udcaa", "Time Created": null, "Time Published": "2022-09-01T14:22:52Z", "Duration": null, "Description": "Going over some benchmarks on Asahi Linux vs MacOS on M1 and M2 Macs. TG Pro for temperature reading and fan control on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GrKCLRUdgdI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Convert NativeScript Imports From v6 to v7", "Time Created": null, "Time Published": "2020-11-13T16:30:01Z", "Duration": null, "Description": "I'm going to show you how to use the new streamlined imports in NativeScript 7 and how to convert NativeScript 6 imports to 7.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "1dJ5bc08C0w", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Animation Wizard William Juan", "Time Created": null, "Time Published": "2020-05-06T17:00:00Z", "Duration": null, "Description": "You've seen his amazing NativeScript animated UI's all over Twitter and on the NativeScript blog. William shares his journey with ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "K_f6YxSUkpE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 Pro and M1 Max Benchmarks | Geekbench 5", "Time Created": null, "Time Published": "2021-10-20T18:55:30Z", "Duration": null, "Description": "Apple's unleashed event just ended where the new MacBook Pro models with M1 Pro and \u200cM1\u200c Max chips were revealed, AND the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TAzQ2_8lFdY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "The Creator of NativeScript-Vue Shows me Routing | NativeScript-Vue Tutorial", "Time Created": null, "Time Published": "2020-05-21T17:00:12Z", "Duration": null, "Description": "In this NativeScript-Vue Tutorial, which is a bonus lesson from the NativeScript Vue Pro course, Igor Randjelovic takes me through ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Ix0bXZeyhK0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Google Login with OAuth2 in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-07-19T11:01:02Z", "Duration": null, "Description": "Do you need to include social logins in your mobile apps? In this NativeScript tutorial, we're using OAuth2 and adding Google ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qhJ4H4EmLzo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to use NativeScript's new Debug + LiveSync feature", "Time Created": null, "Time Published": "2016-08-21T20:29:37Z", "Duration": null, "Description": "In this video tutorial, I show you how you can use the new (as of version 2.2.0) debugging while livesyncing feature that's available ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "VhFAGrKsngs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 Parallels and Windows DOESN'T WORK?", "Time Created": null, "Time Published": "2020-12-29T15:15:14Z", "Duration": null, "Description": "I got really excited to try out Parallels for the Apple M1 chip, since they are the first to market with Apple Silicon support, beating ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "o4H3xTWNsqM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Take it with you | Mac Studio", "Time Created": null, "Time Published": "2022-06-08T18:47:36Z", "Duration": null, "Description": "How I made my Mac Studio portable. #macstudio #m1 #m1ultra.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GBUbmZv8bn0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Select Elements by CSS Class Name in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-10-18T21:13:30Z", "Duration": null, "Description": "Have you wanted to use jQuery selectors in NativeScript? Well, we can come close with the technique I show in this NativeScript ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "F5ZHtJDgM5A", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Translucent Tabs in iOS | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-09-11T03:02:31Z", "Duration": null, "Description": "My guest Dave Coffin shares a technique on making the tab bar translucent in iOS in this NativeScript tutorial. \u25bb SHARE Share ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AbsnFn7A1wM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Commenter Found New Dialog Option | NativeScript Modal", "Time Created": null, "Time Published": "2020-11-09T16:45:00Z", "Duration": null, "Description": "A commenter on this channel recently pointed out to me an option for NativeScript modal dialogs that I didn't know about.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "uFCFdTVAOeg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Converting NativeScript Tutorial to Angular", "Time Created": null, "Time Published": "2020-03-20T13:58:32Z", "Duration": null, "Description": "In this NativeScript tutorial, we convert a custom toggle bar that I created in a previous tutorial (found here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "hA9eYrAlXYw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Scroll to Relative Position or ID in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-04-10T20:23:26Z", "Duration": null, "Description": "In this NativeScript tutorial, I show you how to use a ScrollView to programmatically scroll horizontally to a relative position (start, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "frWHct2uitM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Pro with dock network speed", "Time Created": null, "Time Published": "2022-03-17T16:12:16Z", "Duration": null, "Description": "My current dock: https://amzn.to/3ijmNFH My latest dock with ethernet: https://amzn.to/36a98hz #m1 #m1max #macbook #dock.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xU5TdrNKMHE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Use the Accelerometer Data Stream | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-09-01T11:51:24Z", "Duration": null, "Description": "In this NativeScript tutorial, I'll show you how to use the accelerometer. We'll start off with the basics - how to get the plugin running ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ozhOETzdTgw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Vertically Center Label Text in NativeScript Android Tutorial", "Time Created": null, "Time Published": "2019-03-23T20:20:05Z", "Duration": null, "Description": "The verticalAlignment property doesn't work with Label text in Android in your NativeScript apps. This is really annoying, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dS7GJrodHnM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Custom Dialog in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-08-20T19:33:22Z", "Duration": null, "Description": "In this NativeScript tutorial, I show you how to create your own custom dialog without being tied to the dialogs that come with ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ru60D7P_ZhI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript CLI Info and Runtime Update", "Time Created": null, "Time Published": "2019-10-04T22:11:42Z", "Duration": null, "Description": "NativeScript CLI commands keep growing in capability and number. In this NativeScript tutorial, let's take a look at a couple of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZSEoPZwc2uA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript GridLayout Productivity Tip with VSCode", "Time Created": null, "Time Published": "2019-08-21T11:34:19Z", "Duration": null, "Description": "In this NativeScript tip, Shiva shows how to use VSCode to speed up the editing of GridLayout child rows and columns - which ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "eK_SRVRO-Xo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Pro Shortcomings | Reaction", "Time Created": null, "Time Published": "2022-02-25T16:04:02Z", "Duration": null, "Description": "My reaction to some unique findings about the latest MacBook Pros by another YouTuber. \u25b6\ufe0f it's ugly, but I picked it anyway ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tKbBHpF1sLU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 Large TypeScript Build", "Time Created": null, "Time Published": "2020-12-31T05:20:16Z", "Duration": null, "Description": "Come hang out as I test the Apple M1 MacBook Air vs my Intel Core i9 MacBook Pro vs a brand new Dell XPS 13 with Core i7.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pBUfxC3tHRs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "100% cpu - the room is hot", "Time Created": null, "Time Published": "2022-03-22T19:23:48Z", "Duration": null, "Description": "Regulate fan and get cpu and GPU temperatures with TG Pro: https://a.paddle.com/v2/click/114/137247?link=48 (affiliate) ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cCNIcUq6rVM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Why is Intel i9 BEATING the M1 Max MacBook in THIS test?", "Time Created": null, "Time Published": "2021-10-28T21:21:14Z", "Duration": null, "Description": "Come hang out and help with this enigma. For some reason, this in browser JavaScript test runs faster on the Intel Core i9 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4KWl-Tkp9q4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "WWDC Hardware miss, Giveaway Winner", "Time Created": null, "Time Published": "2021-06-07T20:21:29Z", "Duration": null, "Description": "No hardware this WWDC, and I'm bummed. But here is a winner of the Keychron K8 keyboard!", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9uZfxHPTvk4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Circular Horizontal Scroll in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-04-18T12:15:24Z", "Duration": null, "Description": "In this video installment of #iScriptNative, we continue exploring the horizontal scroll, but this time, we're looping it using our own ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vP9VXle4Pvg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript HMR is Here - and It's On by Default!", "Time Created": null, "Time Published": "2019-05-24T11:36:05Z", "Duration": null, "Description": "Hot Module Replacement in NativeScript is here! And it's turned on by default. In this video, I take it for a test drive in NativeScript ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tcEEKtLeJHw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Vue Directive Part 1: Animation | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-04-03T19:12:01Z", "Duration": null, "Description": "In this NativeScript-Vue tutorial, I'll show you how to create a reusable directive that we'll apply to a card UI. Here we'll create an ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "5uaceQL6Rz8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Get Battery Level Updates in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-10-09T12:50:42Z", "Duration": null, "Description": "In this NativeScript tutorial, I show you: 1. How to translate Android Java code you find on the internet into JavaScript (TypeScript) ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "saVbXpcj1tE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Hired!", "Time Created": null, "Time Published": "2022-06-10T17:54:47Z", "Duration": null, "Description": "If you want to show off your GitHub contributions, and a lot of them are private, be sure to enable this setting. #github.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "MvbTsfssHgQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Brad Martin's thoughts on NativeScript, Developer Health, and Life Balance", "Time Created": null, "Time Published": "2020-04-06T19:15:27Z", "Duration": null, "Description": "Here is a chat I had with Brad Martin, a NativeScript course author and a big contributor to the NativeScript community. This was ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qABgbmuqMBo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "requestAnimationFrame and PAUSING Animation | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-05-14T17:00:23Z", "Duration": null, "Description": "In NativeScript 6.5 a new function has been added that we've been waiting for - requestAnimationFrame. In this NativeScript ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mor88GTm5BE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Create a Color Line Shadow in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-05-20T12:06:10Z", "Duration": null, "Description": "In this video I show you how to get those clean line shadows that you can fully control in intensity, size, and color. And they will ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dJv6zX0vC6Y", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Loading Spinner with CSS NativeScript Tutorial - v2", "Time Created": null, "Time Published": "2019-05-17T11:13:24Z", "Duration": null, "Description": "In this NativeScript video tutorial I'll show you how to replace the ActivityIndicator that comes with the iOS and Android platforms ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "lH04B5o9Am4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Upgrading NativeScript and Your NativeScript Projects to the Latest Version", "Time Created": null, "Time Published": "2016-08-19T23:02:19Z", "Duration": null, "Description": "In this video, I will show you how to upgrade your existing installed version of the NativeScript CLI as well as how to get your ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "019cfHlFfcY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "invite to wwdc2022 in cupertino #short", "Time Created": null, "Time Published": "2022-05-04T16:03:42Z", "Duration": null, "Description": "invite to wwdc2022 in cupertino #short.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FQZI-qit9ME", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "2 Uses for the NativeScript SEARCHCODE Tool", "Time Created": null, "Time Published": "2019-08-09T14:21:42Z", "Duration": null, "Description": "Do you use the NativeScript SearchCode tool? Ok, another question - have you heard of the SearchCode tool? Let's look at two ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "o6CALjTUNSQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Change the iOS Simulator When Running NativeScript Apps", "Time Created": null, "Time Published": "2020-01-21T10:00:15Z", "Duration": null, "Description": "After an update my iPad simulator kept popping up instead of an iPhone simulator when I ran my NativeScript apps. In this video I ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9pWzoonKacQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Controlling Size and Display of NATIVE MODAL Dialogs in iOS | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-02-03T10:00:00Z", "Duration": null, "Description": "In this NativeScript tutorial, we'll continue where we left off in the previous iOS Modal Dialog video and explore two more options ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Lrx06mh7YAc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "2 Methods to Simulate a Slow Network Connection for iOS and Android Development", "Time Created": null, "Time Published": "2020-11-18T16:30:01Z", "Duration": null, "Description": "In this video I'll show you how to set up two tools for helping to simulate a slow network connection when you're developing ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7pdz4SF1VLU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Will Apple Silicon Change Software Development?", "Time Created": null, "Time Published": "2020-12-08T15:00:03Z", "Duration": null, "Description": "Is the new Apple Silicon M1 chip be good for Mac users and PC users? Here are my thoughts on how this impacts us, software ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "fC4ZRh0L2No", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Error After Xcode Update", "Time Created": null, "Time Published": "2019-11-22T10:00:06Z", "Duration": null, "Description": "Updating software is sometimes (most of the time these days) a scary thing. You never know if there will be incompatibilities that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rNe4UJD216A", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Platform Specific Functions in NativeScript", "Time Created": null, "Time Published": "2018-01-22T13:11:05Z", "Duration": null, "Description": "In this second video of the series, I show you how to execute different code while calling a single function. If you need to execute ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "W4WJPcBp12k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Nathan Walker - NativeScript Contributor and a Well Rounded Dev", "Time Created": null, "Time Published": "2020-05-19T17:00:09Z", "Duration": null, "Description": "In this NativeScript chat, Nathan Walker joins me to discuss his journey through web development and how he got to NativeScript.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "u6NlyUSGmmU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple M1 vs Intel Core i9 and .NET Performance - First Look", "Time Created": null, "Time Published": "2021-01-04T15:00:30Z", "Duration": null, "Description": "In this video I take a look at .NET performance on the Apple Silicon M1. I do a few quick speed comparisons of a console ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "VKbwdivM6Eg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Modal Dialog Blur Animated Transition in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-12-31T10:00:06Z", "Duration": null, "Description": "There is a way to open the native modal dialogs in iOS by specifying a transition animation. In this NativeScript tutorial, I'll show ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mC8CUNFfiCU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I build the quietest PC using APPLE SILICON!", "Time Created": null, "Time Published": "2022-04-01T13:06:45Z", "Duration": null, "Description": "macstudio #m1ultra #m1.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "nHWPbZEsLPo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Show and Hide the Status Bar with Animation | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-07-16T05:22:35Z", "Duration": null, "Description": "The status bar has been one of the most difficult UI elements to control in NativeScript because it is so different on iOS and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "RCIajqLNems", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "is it TIME to START thinking about this?", "Time Created": null, "Time Published": "2022-04-25T18:32:10Z", "Duration": null, "Description": "How Apple Silicon opened my eyes to an ongoing issue and lit a new way forward. #applesilicon #m1 \u25b6\ufe0fMy recent tests of M1 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ySFWy0vWgO8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript From Scratch Part 2: TypeScript and Webpack Configuration", "Time Created": null, "Time Published": "2020-02-13T16:12:57Z", "Duration": null, "Description": "In this NativeScript tutorial, we'll pick up where we left off in part 1 and incrementally add TypeScript to our JavaScript mobile app ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "26KWxgc_RIQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Page Indicator in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-07-02T13:57:45Z", "Duration": null, "Description": "In this NativeScript tutorial, I show you how I built the animated page indicator from scratch using only JavaScript, CSS, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AL_8bsBjYuU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript-OAuth2 Plugin Update Live Stream Wrap-up", "Time Created": null, "Time Published": "2020-09-14T13:19:47Z", "Duration": null, "Description": "A few days ago, Nathan Walker and I did a live stream here (link below) and we upgraded the NativeScript-OAuth2 plugin to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ieEupME02Kw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript JavaScript Compatibility Tool Overview", "Time Created": null, "Time Published": "2019-06-11T11:22:22Z", "Duration": null, "Description": "The new NativeScript JavaScript (ECMAScript) Compatibility Tool is available here: http://nativescript.rocks/compat \u25bb SHARE ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cDJaIgBimCc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Match NativeScript Shadows in iOS and Android | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-03-24T16:41:38Z", "Duration": null, "Description": "There are different ways to add shadows to views in your NativeScript apps in iOS and Android, and I show both in the linked ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "RgIpDc9gdQU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Floating Action Button in NativeScript with Angular. Part 5: Bonus Round", "Time Created": null, "Time Published": "2017-02-01T02:13:26Z", "Duration": null, "Description": "In this bonus round, I'll show you how to add a shadow to the Android and iOS implementations of the FAB using native calls with ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "k79y1Ec-XzU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "HTTPS Debugging Your Mobile Apps", "Time Created": null, "Time Published": "2020-11-02T13:55:21Z", "Duration": null, "Description": "In this video, I show how to decrypt HTTPS traffic going to and from your iOS device or simulator using a tool called Charles.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rskUWZi3pyQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Exploring NativeScript Plugins: Numeric Keyboard", "Time Created": null, "Time Published": "2020-06-26T16:45:01Z", "Duration": null, "Description": "In this first of the NativeScript plugins series, I show you how to set up an input to display a numeric keyboard instead of the usual ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "zE2O_BmcBr4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "intel macbook low battery #short", "Time Created": null, "Time Published": "2022-01-17T21:12:09Z", "Duration": null, "Description": "Just a bit of fun. Everyone needs some. Hope everyone's having a good day. #macbook #intel.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ayJkD-JzdE4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac Studio M1 Ultra Unboxing and vitals tests", "Time Created": null, "Time Published": "2022-03-18T19:33:42Z", "Duration": null, "Description": "Come hang out and let's unbox the new Mac Studio.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "wlfUM45hQJo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Alpha VS. Opacity in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-11-08T10:00:18Z", "Duration": null, "Description": "Did you know that using alpha transparency is going to give you different results than using opacity both with the look and the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "5I1s6rCKIno", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Air M2 \ud83d\udd34 Unboxing and Initial Tests", "Time Created": null, "Time Published": "2022-07-15T20:14:12Z", "Duration": null, "Description": "Come hang out and let's unbox the new M2 MacBook Air Apple unveils all-new MacBook Air, supercharged by the new M2 chip ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6q7cIxVsVVA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "2021 MacBook Pro 16" and 14" unboxing", "Time Created": null, "Time Published": "2021-10-26T20:32:07Z", "Duration": null, "Description": "Come hang out and help me unbox these M1 Pro and M1 Max MacBook Pros. We'll also plan out some upcoming videos for ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pW9X-ygrvEY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Shapes | 2 Methods for Creating Shape Views", "Time Created": null, "Time Published": "2019-05-22T16:21:40Z", "Duration": null, "Description": "In this NativeScript tutorial I show you two methods for creating custom shapes in your UI. We're going to be doing more ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vz7qfpeghFs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Native TypeScript PLATFORM DECLARATIONS in NativeScript", "Time Created": null, "Time Published": "2019-09-06T18:58:48Z", "Duration": null, "Description": "When writing JavaScript, or more specifically TypeScript code in NativeScript, you can use native iOS and Android APIs directly.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6zBbYbn4Cvs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Image Blur in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-12-24T10:00:00Z", "Duration": null, "Description": "A nice little technique for blurring images. This NativeScript tutorial shows you how to do it in iOS and Android while maintaining a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cKevwkBQA5Q", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "where is MY DATA?!!! \ud83e\udd2c", "Time Created": null, "Time Published": "2022-06-14T14:36:42Z", "Duration": null, "Description": "I tried recovering my data from these drives. It went like this... The thing I used to read the old drives: https://amzn.to/3MRfRfQ ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4GHT8yD94Us", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Transparent Gradient Fix", "Time Created": null, "Time Published": "2020-09-29T15:30:01Z", "Duration": null, "Description": "I recently ran into a problem with using transparent as one of the gradient stop in a linear gradient in NativeScript. In this video I ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ngPj3E5wSOA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple WWDC 2021 - NEW MacBook Pros, M1X, and Other Goodies", "Time Created": null, "Time Published": "2021-06-05T20:24:27Z", "Duration": null, "Description": "Apple WWDC 2021 is rumored to announce new MacBook Pros, with M1X or M2 chips. These will be a brand new MacBook Pro ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8Q8OtgL3Fuo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Tutorial for Beginners - Build iOS, Android and Web Apps with NativeScript", "Time Created": null, "Time Published": "2020-03-11T18:36:43Z", "Duration": null, "Description": "This NativeScript tutorial for beginners will get you started with NativeScript Core using TypeScript. NativeScript is a cross-platform ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "34JuCtyb51Q", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Animate TEXT COLOR in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-08-02T17:31:35Z", "Duration": null, "Description": "Finally we can animate text color in NativeScript using JavaScript animations! This is not built into NativeScript CSS or the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "132ufSPXcXs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "React NativeScript CLI Update", "Time Created": null, "Time Published": "2020-06-30T12:07:16Z", "Duration": null, "Description": "The new kid on the block - React NativeScript - gets official support from the NativeScript CLI. Meet the CREATOR of REACT ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "eVK8QGOQ5zc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "m2 macbook air unboxing", "Time Created": null, "Time Published": "2022-07-29T11:30:10Z", "Duration": null, "Description": "With a nice soundtrack #m2 #macbookair #macbookair2022 music by Aphex Twin.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rZMInRj2Mnk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple unleashed M1 Pro and M1 Max AND new MacBooks! CONFIRMED \ud83d\ude00", "Time Created": null, "Time Published": "2021-10-18T20:02:03Z", "Duration": null, "Description": "The wait is over, and Apple announced two new SoC silicon boards: M1 Pro and M1 Max. These will be in the new redesigned ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Q3pyDmAT6eQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "this channel is changing", "Time Created": null, "Time Published": "2022-01-29T17:20:02Z", "Duration": null, "Description": "Here's what's new with the channel. Members welcome. Join the channel: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4lhEe3oCNMc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "MacBook Pro wins 2022", "Time Created": null, "Time Published": "2022-01-13T16:53:05Z", "Duration": null, "Description": "We saw the upcoming laptop contenders at CES 2022, and seems that the 2021 MacBook Pros will still reign in 2022. Related ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "evRUaPtg4TE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Insert a Line Break Using a FormattedString in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-05-06T11:18:33Z", "Duration": null, "Description": "Whether you're using NativeScript Core, NativeScript Vue, or NativeScript Angular, some core widget tricks are the same, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xBfZ2-0U4ck", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "\ud83d\udd34Unboxing MacBook Pro M2", "Time Created": null, "Time Published": "2022-06-24T20:13:11Z", "Duration": null, "Description": "Come hang out and let's unbox the new M2 MacBook Pro The MacBook Pro 2022 comes with the latest M2 chip. While the M2 ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "5K44bAASHTs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "I\u2019m an imposter", "Time Created": null, "Time Published": "2021-07-15T14:06:30Z", "Duration": null, "Description": "Sometimes I feel like I don't know what I'm doing - like I'm an imposter. This is pretty common among software developers and it's ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "V0doxN0gkoI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Facebook Login with NativeScript", "Time Created": null, "Time Published": "2017-01-09T02:27:23Z", "Duration": null, "Description": "In this video tutorial, you will learn how to use the nativescript-oauth plugin to login into Facebook in your NativeScript mobile ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Wf5CHJZdkro", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "New M1 Pro and M1 Max MacBooks and other options", "Time Created": null, "Time Published": "2021-10-21T20:21:59Z", "Duration": null, "Description": "A roundup of the current MacBook lineup that we can get our hands on, along with price and configuration comparisons for ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "SLSe9mrUz6c", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel: Running More .NET Tests Based on Your Comments", "Time Created": null, "Time Published": "2021-01-18T17:35:54Z", "Duration": null, "Description": "I'm continuing testing the M1 MacBook and comparing it to the Intel MacBook. In this video the let's do another .NET test on each ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cKzm14khSx8", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Building an Animated NativeScript Progress Bar (Part 1)", "Time Created": null, "Time Published": "2018-07-30T16:29:47Z", "Duration": null, "Description": "This is the first part of a series of videos where I show how to build a progress bar in NativeScript. We'll go from a progress bar that ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "btq7D7w81C0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Platform Specific Classes in NativeScript", "Time Created": null, "Time Published": "2018-01-19T03:22:39Z", "Duration": null, "Description": "In this first video of the series, I show you how to separate out your platform specific code using TypeScript classes. If you need to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "r7o5GBpGYJI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Modal Dialog from a SERVICE in NativeScript-Vue | Tutorial", "Time Created": null, "Time Published": "2019-11-27T10:00:10Z", "Duration": null, "Description": "Opening a native iOS or Android native modal dialog in NativeScript-Vue is pretty simple thanks to the functions that live on Vue ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "zya37YNqIH0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your NativeScript Apps and Contest Vote", "Time Created": null, "Time Published": "2020-05-26T17:00:25Z", "Duration": null, "Description": "A few weeks ago you sent me screenshots of your awesome apps. Thank you! I selected the top 10. Now you get to vote for your ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BK6Ab9Kb2oI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Can you even get a new MacBook? | M1, M1 Pro/Max", "Time Created": null, "Time Published": "2021-12-13T20:01:01Z", "Duration": null, "Description": "You can get a new MacBook today or you have to wait two months. Configuration options and delay times mapped. \u25b6\ufe0fMy recent ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "C6YFLsoVGjA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: M1 With Go and giveaway!", "Time Created": null, "Time Published": "2021-05-27T19:40:04Z", "Duration": null, "Description": "Come hang out and test Go and Hugo on the M1 Mac with Nic Raboy and me. You can get in touch with Nic here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "USgmxvinIaM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "programmer q&a and giveaway winner", "Time Created": null, "Time Published": "2021-07-23T15:14:49Z", "Duration": null, "Description": "Welcome to the first ever q&a on this channel. More videos that you might enjoy: \u25b6\ufe0f is software engineering hard?", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cBPRPSEv8wI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Backend Poll Results and Giveaway", "Time Created": null, "Time Published": "2020-05-08T17:00:13Z", "Duration": null, "Description": "A little while ago I asked you to tell me what backend technology you use. This is for NativeScript backends, but I'm sure has more ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "LHYkoUNXMJ0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Floating Action Button in NativeScript with Angular. Part 4: Adding the Finishing Touches", "Time Created": null, "Time Published": "2017-01-26T13:40:48Z", "Duration": null, "Description": "Finally, in part 4 of the tutorial, you will make the user feel like they are actually tapping on a button. I show you how to use ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "M42Xl2PWzLc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "iPhonization of the Mac: Is Apple's M1+ a Marketing Move?", "Time Created": null, "Time Published": "2021-02-05T17:11:42Z", "Duration": null, "Description": "Some thoughts about what Apple is doing with Apple Silicon, and some subsequent questions about their plans. You can also ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZRNSIJarNco", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: M1 With Go and giveaway!", "Time Created": null, "Time Published": "2021-05-21T19:45:14Z", "Duration": null, "Description": "Come hang out and test Go on the M1 Mac with me. Thanks for watching! Please like, comment, & subscribe.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZRNSIJarNco", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: M1 With Go and giveaway!", "Time Created": null, "Time Published": "2021-05-21T19:45:14Z", "Duration": null, "Description": "Come hang out and test Go on the M1 Mac with me. Thanks for watching! Please like, comment, & subscribe.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dIw_TvgVolg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "10000 Thanks!", "Time Created": null, "Time Published": "2021-01-22T17:01:00Z", "Duration": null, "Description": "This channel reached 10000 subscribers! Thank you all who have supported me and liked my videos, commented, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DnrsvVcbUxM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is Intel i9 BEATING the M1 Max in C++ too? WHY?!!", "Time Created": null, "Time Published": "2021-11-02T19:43:17Z", "Duration": null, "Description": "I've got another puzzle. Just found that running this c++ test on the new M1 Max is slower than on the Intel i9 MacBook Pro. What's ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7erSB-i0KNY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Filtering Console Output", "Time Created": null, "Time Published": "2020-11-11T16:15:01Z", "Duration": null, "Description": "In this video I'll show you two methods for filtering console output from your NativeScript apps, as well as. any mobile app running ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "3aZ5AZVNbbY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "FULLSCREEN VIDEO | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-02-21T10:00:00Z", "Duration": null, "Description": "In this NativeScript Tutorial I show you how to add videos to your NativeScript apps, and then how to make those videos stretch ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vX33lc4BIG0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript 6 and 7 Compatibility", "Time Created": null, "Time Published": "2020-10-23T18:35:46Z", "Duration": null, "Description": "In this video I break down the different puzzle pieces of what \"NativeScript\" is: the core library, the NativeScript runtime, and the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "ZLP4Nt6lAJQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Joins OpenJS Foundation", "Time Created": null, "Time Published": "2020-12-10T12:20:12Z", "Duration": null, "Description": "Have you heard the news? NativeScript joins OpenJS Foundation as one of it's incubating projects. What does this mean for the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "fGDLjePyQTU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Async Await in NativeScript", "Time Created": null, "Time Published": "2018-09-30T14:39:30Z", "Duration": null, "Description": "In this tutorial I show you how to use async/await in NativeScript. We start from scratch using the Angular template (just because it ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "2JDXnduTlgs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Hello World native iOS mobile app using TypeScript and NativeScript", "Time Created": null, "Time Published": "2016-01-24T18:10:42Z", "Duration": null, "Description": "This tutorial demonstrates how to convert the JavaScript generated by the NativeScript hello world template back into TypeScript.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "brNrT336-YE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Animated Hamburger Button | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-07-23T17:05:14Z", "Duration": null, "Description": "The quintessential animated hamburger in NativeScript tutorial is HERE. This is just one example of what you can do using just ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "n8O9JUybAcs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "downside of macbook reviews", "Time Created": null, "Time Published": "2022-10-03T15:57:47Z", "Duration": null, "Description": "m2 #macbook #macbookair.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "el3TfNtlgOE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Mac Studio and PC Oscars night (Will Smith and Chris Rock Parody)", "Time Created": null, "Time Published": "2022-03-28T16:36:02Z", "Duration": null, "Description": "", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tO4rxvE5opQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Animate Text in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-06-08T18:11:06Z", "Duration": null, "Description": "In this NativeScript tutorial, we're animating text to simulate a typewriter effect. This can be used to display text, placeholders, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "TwBb696SjqA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Password Hashing and JWTs: Lesson from NativeScript Security Course", "Time Created": null, "Time Published": "2019-03-30T12:30:16Z", "Duration": null, "Description": "In this video I share a lesson from the recent course published on NativeScripting.com called Securing NativeScript Applications.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AVWhrRRZQ9A", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript 6.4 New Feature 3D ROTATION! | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-02-14T10:00:03Z", "Duration": null, "Description": "With NativeScript 6.4 we got an awesome new feature - 3d rotation. In this NativeScript tutorial, I'll show you how you can use it in ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "jLz5wAsKni0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "CENTERING Things in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-10-02T20:41:31Z", "Duration": null, "Description": "In this NativeScript tutorial, I'll show you how to center elements in NativeScript using layouts, properties, and CSS. (Thumbnail ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "GEbUs7pf-no", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple Store Button with ContentView | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-12-05T10:00:02Z", "Duration": null, "Description": "In this NativeScript tutorial, we're ditching boring buttons and replacing them with clever, creative, stylish buttons (inspired by the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "8iLR4swFhzw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Take a SCREENSHOT in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-03-10T16:46:29Z", "Duration": null, "Description": "If you've ever had the need to capture a UI view or a hierarchy of views as a screenshot and save it to the file system or display it, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "jHIeWCN6yXY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Tracing in NativeScript Apps", "Time Created": null, "Time Published": "2019-05-13T11:40:23Z", "Duration": null, "Description": "Using console.log() a lot? Have better control of your knowledge about your mobile application by incorporating tracing in your ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DQaI7lmXT8Q", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript 4.1 Gradients", "Time Created": null, "Time Published": "2018-06-02T20:01:06Z", "Duration": null, "Description": "There is a brand new feature that we get when we upgrade to NativeScript 4.1 - CSS gradients! Gradients is a feature we've been ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "wZU0vbxWriE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your NativeScript Wish List", "Time Created": null, "Time Published": "2020-09-21T15:30:01Z", "Duration": null, "Description": "We have a few items that we wish NativeScript had built-in. This video is a review of wish list items you mentioned and things I ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FW6chOaMvuo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Scoped NPM Packages", "Time Created": null, "Time Published": "2019-12-02T14:02:55Z", "Duration": null, "Description": "Scoped NPM packages are all the rage these days - BECAUSE THEY ARE AWESOME. Scoped packages are new to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "JCYzlwFZn0E", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "What's Coming in 2020", "Time Created": null, "Time Published": "2020-01-16T10:00:05Z", "Duration": null, "Description": "In this video I share a quick update about what to expect from me in 2020. I'll talk about my YouTube channel, my outside work, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "u7BQksdfoJo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: NativeScript 7 Plugin Update with Nathan Walker", "Time Created": null, "Time Published": "2020-09-10T13:57:25Z", "Duration": null, "Description": "On this live stream, Nathan Walker and Alex Ziskind will update a pre-NativeScript 7 plugin.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "6cRY3khXMmE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Intro to the New World of NativeScript Contributing", "Time Created": null, "Time Published": "2020-08-26T19:52:12Z", "Duration": null, "Description": "With the latest release of NativeScript, contributing to the framework has become a simple task. In this video, I'll show you how to ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "HmYYQAayOt0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Timeline Profiling in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-10-30T11:42:20Z", "Duration": null, "Description": "Let's look at a useful tool for troubleshooting performance issues in NativeScript apps - this is the timeline-view tool. I'll show you ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "-ni_DYLbGHE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Detect ListView Scroll Events in NativeScript | Tutorial | Part 1", "Time Created": null, "Time Published": "2020-07-06T16:00:01Z", "Duration": null, "Description": "In this NativeScript tutorial, which is a video lesson from the NativeScript Core Pro course (link below), I show you how to use ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "CVZDURL8HWs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Create iOS Podcast Cover Art Animation with Inheriting Shadow Color | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-08-30T08:30:01Z", "Duration": null, "Description": "In this NativeScript Tutorial we're recreating the play/pause animation that's used in iOS podcasts app. This is an iOS only tutorial ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "kXOY_KUEHWY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "2 Types of Android Shadows NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-02-28T10:00:15Z", "Duration": null, "Description": "In this NativeScript tutorial, I'll show you 2 techniques for adding shadows to views on Android. If you want iOS - see this video: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qhXXL8wUGZM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Migrating My Project to NativeScript 6", "Time Created": null, "Time Published": "2019-07-30T15:04:07Z", "Duration": null, "Description": "Since NativeScript 6 comes with a significantly different workflow than its predecessors, It's time to update all the courses on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "xmYqQJBxWxk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Reading About Your Favorite NativeScript Plugins", "Time Created": null, "Time Published": "2020-11-19T14:05:31Z", "Duration": null, "Description": "I asked what were your favorite NativeScript plugins, and some of you replied. THANKS! Here is what you said. NativeScript ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "R6eA8yupaAk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Do Binding Using $value in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-09-27T16:05:10Z", "Duration": null, "Description": "In this NativeScript tutorial, I'll show you how to get the binding context in the view, also known as $value. \u25bb Global vs.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "psPybqKm_Gg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Develop Software? Don't Forget to Take Get Up and Move Around", "Time Created": null, "Time Published": "2020-10-14T15:18:57Z", "Duration": null, "Description": "Just a reminder that you need to feed your brain fresh air and downtime to be productive as a mobile application developer and as ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "I3fgyYArzqk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to get Top UI Element without ID in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-10-16T15:35:04Z", "Duration": null, "Description": "Sometimes getting the topmost frame in NativeScript doesn't mean that you got a reference to the Frame element at the top of the ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "9h10rq_BJlM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Use Origin Point in NativeScript Animation", "Time Created": null, "Time Published": "2019-09-26T14:57:14Z", "Duration": null, "Description": "When you use NativeScript Animation you can set an originX and originY to control where the animation originates - as I show you ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "DBqMv4urH5E", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Add SHADOWS in iOS | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-08-13T20:38:41Z", "Duration": null, "Description": "Ah the elusive and quite popular shadows for views! In this NativeScript tutorial, I'll show you 5 properties you can alter to create ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "4rXdmRhkhkI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Custom FAB with CSS in NativeScript Tutorial - UPDATE", "Time Created": null, "Time Published": "2019-07-09T10:43:41Z", "Duration": null, "Description": "It's time to update the old FAB (Floating Action Button) tutorials that I posted about two years ago here. We're still using just CSS, ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "88C3XpJn81k", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Using the Font Icon Plugin (2/2) - NativeScripting Angular Pro Course Preview", "Time Created": null, "Time Published": "2018-03-26T13:53:24Z", "Duration": null, "Description": "This lesson shows how to implemented font icons using a font icon plugin. It builds on the previous lesson where we already ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Fv0lcsKA7SY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Testing Best JavaScript Framework on my Apple Silicon Mac", "Time Created": null, "Time Published": "2022-05-27T18:53:02Z", "Duration": null, "Description": "Come hang out and let's run some JavaScript tests.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7_5PCAtWOFM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "What\u2019s he building?", "Time Created": null, "Time Published": "2022-03-24T22:39:35Z", "Duration": null, "Description": "", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "fP672ySsxxM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "upgrading RAM in MacBook Pro", "Time Created": null, "Time Published": "2022-02-07T19:25:05Z", "Duration": null, "Description": "", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "lNcNYFNEaEI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Observable Magic String Property Names, Be Gone!", "Time Created": null, "Time Published": "2017-12-07T21:02:07Z", "Duration": null, "Description": "When developing NativeScript Core apps, we often have to update our Observable properties using a magic string, instead of a ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "yGIrk24FPJw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Question for You About NativeScript", "Time Created": null, "Time Published": "2020-09-09T15:12:46Z", "Duration": null, "Description": "Please let me know your biggest burning question about NativeScript here: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "JilBilnwx7M", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript App Audit NO $$$", "Time Created": null, "Time Published": "2020-02-25T11:00:03Z", "Duration": null, "Description": "Let's do an audit of your app! Free NativeScript Training Webinar: https://nativescripting.com/pro-webinar Nuvious - My client ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "7i5AGfF2CK0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "3000 Thank You's", "Time Created": null, "Time Published": "2020-03-25T18:34:23Z", "Duration": null, "Description": "We've reached 3000 subscribers on this channel. It's hard to believe it, but yeah, we did it. Thank you all who have supported me ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "cKP1YRzMahM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Poll - What's Your Backend?", "Time Created": null, "Time Published": "2020-02-17T15:33:54Z", "Duration": null, "Description": "Please let me know in the comments or on Twitter (@digitalix) what backend you're using with your NativeScript apps. Cheers!", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "rkBpzQ5qRpg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple Silicon M1 Performance for Developers Tests Coming Soon", "Time Created": null, "Time Published": "2020-11-26T14:42:50Z", "Duration": null, "Description": "I've recently ordered the new Macs with the M1 chip - really curious to do some performance tests for mobile development on ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "C-twSGVLQcw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Global vs. Local Converters in NativeScript Core", "Time Created": null, "Time Published": "2019-03-27T11:34:55Z", "Duration": null, "Description": "In this video, Shiva Prasad teaches you all about NativeScript converters. The difference between global and local converters as ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "mNCIFP9QIw0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Meet Josh Sommer - Software Developer", "Time Created": null, "Time Published": "2020-11-15T14:49:29Z", "Duration": null, "Description": "In this NativeScript chat, Josh Sommer joins me to discuss his journey through web development, how he got to NativeScript, and ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "V3e-ek2fpSY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "React to Property Changes in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-06-03T11:05:20Z", "Duration": null, "Description": "In NativeScript Core apps, we have to listen for changes in observables in order to get notified of property changes. In this ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "FB3PN-FZ6qI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Using NativeScript Snippets", "Time Created": null, "Time Published": "2018-07-06T12:39:48Z", "Duration": null, "Description": "This is another time-saving tip for NativeScript developers. If you aren't using NativeScript Core and NativeScript Angular snippets ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Pz_1fuZ_ft0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Upgrading to NativeScript 2.5, pitfalls and all", "Time Created": null, "Time Published": "2017-02-02T15:59:08Z", "Duration": null, "Description": "NativeScript is constantly getting improved by the hard working core team and we have to stay on top of the latest and greatest ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "eyPGbzu3csI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 Browser JavaScript Speed Tests", "Time Created": null, "Time Published": "2020-12-23T10:06:59Z", "Duration": null, "Description": "In this live stream, I'll run a custom JavaScript function and execute it in the browser. Then I'll use a benchmarking tool (website) ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "tVsSx0weQWA", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 vs Intel i9 vs ? - Angular Build Race", "Time Created": null, "Time Published": "2020-12-31T04:46:29Z", "Duration": null, "Description": "Come hang out as I test the Apple M1 MacBook vs My Intel Core i9 MacBook Pro vs a brand new laptop I just picked up for these ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "LqXsCYH589A", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "testing stream", "Time Created": null, "Time Published": "2020-06-21T19:32:40Z", "Duration": null, "Description": "", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Hevpz0EQe5s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your Best Tips and Tricks Contest", "Time Created": null, "Time Published": "2020-12-03T14:59:25Z", "Duration": null, "Description": "Do you have tips and tricks to share? Send them over to me and I may feature your tip (and your project) here. The new ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "NHL_tS2juj4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Your NativeScript App Contest with PRIZES", "Time Created": null, "Time Published": "2020-05-07T17:00:09Z", "Duration": null, "Description": "Rules: Send me your NativeScript app screenshot - one that hopefully you're proud of - by May 15, 2020. We'll vote on a winner ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "15mmpf6sZ7s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Tyler Blake on NativeScript with .NET and Azure", "Time Created": null, "Time Published": "2020-04-20T11:40:30Z", "Duration": null, "Description": "Here is my chat with Tyler Blake, a full stack engineer, author on NativeScripting, and a long time NativeScript developer.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "akh6Vs-HXRE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Community Spotlight - Tiago Alves", "Time Created": null, "Time Published": "2020-02-24T10:00:00Z", "Duration": null, "Description": "Continuing my chats with NativeScript community members, here's my chat with Tiago Alves, a NativeScript Vue guru, a speaker ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Z-m5clyhTwY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Rowdy on NativeScript, Full Stack, and Constant Learning", "Time Created": null, "Time Published": "2020-05-11T17:00:15Z", "Duration": null, "Description": "Rowdy Rabouw joins me for a NativeScript community chat, where we discuss his career path, his coding experience, and what ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "_Sjv6rNm-SQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "3 NativeScript Animation Timing Techniques | NativeScript Tutorial", "Time Created": null, "Time Published": "2020-05-29T15:47:39Z", "Duration": null, "Description": "In this NativeScript tutorial, I show you three methods for making your animations more life-like and realistic by adding timing ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "COXOOrNYB7s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Securing NativeScript Applications Course in 30 seconds", "Time Created": null, "Time Published": "2019-01-03T03:20:42Z", "Duration": null, "Description": "This is an exciting new course coming out in about a week.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Y0mw3AeSlQE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "New NativeScripting Graphic Poll", "Time Created": null, "Time Published": "2020-04-21T10:00:18Z", "Duration": null, "Description": "Just a quick poll about which new Nativescripting graphic looks best. Nuvious - My client business \u2014 https://www.nuvious.com ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "dtwz0gQWcKs", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScripting Angular Pro Course - Modal Dialog Checklist", "Time Created": null, "Time Published": "2018-03-01T14:25:19Z", "Duration": null, "Description": "This is the checklist for implementing a modal dialog in a NativeScript with Angular application. It is an excerpt from Chapter 6 of ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qgwdN97LANo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Floating Action Button in NativeScript with Angular. Part 2: Creating and Styling the FAB Component", "Time Created": null, "Time Published": "2017-01-26T13:38:04Z", "Duration": null, "Description": "In part 2 of this tutorial, I show you how to create and style the actual floating action button component. Don't skip part 1 though ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PyYrHbSG1oc", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 Pro/Max Unity Testing Brainstorming", "Time Created": null, "Time Published": "2021-11-12T20:35:09Z", "Duration": null, "Description": "Come hang out and let's figure out a good way to test Unity on these new machines.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "CUqNevzfbjQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How will the Cursor behave on the MacBook Pro Notch? | FUNNY with SOUND", "Time Created": null, "Time Published": "2021-10-22T16:52:02Z", "Duration": null, "Description": "How will the MacBook pro handle the notch? Minimal nerd's original vid: https://www.youtube.com/watch?v=iUNeRxzrubw ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "OS75l9AoKPQ", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Creating a Custom Toggle Bar in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-01-27T10:30:00Z", "Duration": null, "Description": "In this NativeScript Tutorial, we're creating a custom toggle bar to replace the SegmentedBar that comes with NativeScript.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "X-4aZ4flv2s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: GitHub Copilot", "Time Created": null, "Time Published": "2021-07-15T20:03:47Z", "Duration": null, "Description": "Come hang out and test GitHub Copilot with me Thanks for watching! Please like, comment, & subscribe.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "IL5bUu5EtVI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Animation Techniques Pluralsight Course Overview", "Time Created": null, "Time Published": "2017-03-03T12:00:51Z", "Duration": null, "Description": "I'm really excited to share with you techniques to make your NativeScript with Angular 2 applications REALLY shine by adding ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Ji9f9DGw894", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 Flutter", "Time Created": null, "Time Published": "2021-04-24T02:31:27Z", "Duration": null, "Description": "Come hang out as I test the Apple M1 MacBook Air vs my Intel Core i9 MacBook Pro. We'll test out Flutter. Thanks for watching!", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "AFEVF8G84SI", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Meet the CREATOR of NativeScript-Vue - Igor Randjelovic", "Time Created": null, "Time Published": "2020-02-01T13:36:46Z", "Duration": null, "Description": "This is a short little meet and greet with the creator of NativeScript-Vue, Igor Randjelovic. Come say 'hi' to him in the comments ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "00Ft3PnYBA4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: NativeScript Angular 9+", "Time Created": null, "Time Published": "2020-07-02T00:30:54Z", "Duration": null, "Description": "Hi NativeScript Angular folks. Nathan Walker of nStudio and I are going to be doing a live stream this coming Wednesday showing ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "PdFgnTmSwn0", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Apps from Scratch", "Time Created": null, "Time Published": "2016-02-07T14:19:40Z", "Duration": null, "Description": "Look Ma, No Templates! This tutorial shows you how to start your NativeScript apps without using templates. I show you how you ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "z8O0twgfo8U", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: M1 vs Intel MacBook in Angular (JavaScript) Build on a Linux VM in Parallels (whew)", "Time Created": null, "Time Published": "2021-04-22T17:10:28Z", "Duration": null, "Description": "In this live stream, I'll compare the M1 MacBook Air with the Intel MacBook Pro setting up a Linux virtual machine in Parallels ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "QkipbelGqKU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 JavaScript Benchmarking", "Time Created": null, "Time Published": "2021-01-08T05:39:27Z", "Duration": null, "Description": "Come hang out as I test the Apple M1 MacBook Air vs my Intel Core i9 MacBook Pro. We'll see which one is faster doing some ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "S9_mzIcERMk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Is Apple's Self Service Repair Program Self Serving?", "Time Created": null, "Time Published": "2021-11-17T17:27:59Z", "Duration": null, "Description": "Apple's Self Service program has been announced as (likely) a direct result of pressure from small businesses and government.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "v5g6irUI704", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Platform Specific CSS in NativeScript", "Time Created": null, "Time Published": "2018-01-25T13:03:21Z", "Duration": null, "Description": "In this third video of the series, I show you how the best way I found so far to separate out your platform specific CSS code, while ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "Kwo8GarqS-s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "4 Tips on Using Accessibility in NativeScript Apps", "Time Created": null, "Time Published": "2020-05-04T17:00:10Z", "Duration": null, "Description": "It's important to make your mobile apps accessible. NativeScript has limited support for accessibility, but we can still make our ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "CmUF6nxY7vk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Faking CSS Overflow in NativeScript Tutorial", "Time Created": null, "Time Published": "2019-04-07T12:35:48Z", "Duration": null, "Description": "NativeScript doesn't have an native CSS overflow property. We're so used to this property on the web that we sometimes structure ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "bHOYL_YpbQE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Dave Coffin on Building the Daily Nanny App in NativeScript, and Using Native APIs", "Time Created": null, "Time Published": "2020-03-30T19:33:12Z", "Duration": null, "Description": "Here is a chat I had with Dave Coffin, a NativeScript tutorial contributor on this channel and an author on NativeScripting.com.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "qnS4NC3Fi_g", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Peek at M1 Ultra and Mac Studio \ud83d\ude00", "Time Created": null, "Time Published": "2022-03-08T21:42:58Z", "Duration": null, "Description": "Apple announces new chip: the M1 Ultra, and a new desktop computer: Mac Studio. Here's a peek. Fireship video: ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "OGoCNPssPZg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Animation of ANY View Property", "Time Created": null, "Time Published": "2019-05-28T13:17:14Z", "Duration": null, "Description": "You can animate any view in NativeScript and any property, not just the ones that CSS exposes or the NativeScript Animation API ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "BUMWje2MtLo", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Building an Animated NativeScript Progress Bar (Part 3)", "Time Created": null, "Time Published": "2018-07-30T16:30:02Z", "Duration": null, "Description": "This is the third video in the series about building an animated progress bar in NativeScript with Angular.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "UBcgsWozsiY", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: M1 With Docker and giveaway!", "Time Created": null, "Time Published": "2021-05-07T19:17:50Z", "Duration": null, "Description": "Come hang out and test the latest version of Docker on the M1 Mac with me. Thanks for watching! Please like, comment ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "aa--J-wscOk", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "M1 MacBook vs Intel i9 and i7 Running JavaScript CPU MAXING Benchmark Test", "Time Created": null, "Time Published": "2021-02-04T16:09:43Z", "Duration": null, "Description": "We'll keep rolling with this series covering the performance of the new Apple M1 Macs for software developers vs my MacBook ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "gRxCGU5RY3s", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Tips for Accessing XML properties in NativeScript | Tutorial", "Time Created": null, "Time Published": "2019-07-25T17:21:10Z", "Duration": null, "Description": "My regular guest Shiva shows how to create custom properties in NativeScript UI Widgets and then how to access those ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "pYJxfziQjT4", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Apple to Unveil Redesigned MacBook", "Time Created": null, "Time Published": "2021-10-15T11:31:59Z", "Duration": null, "Description": "Oct.13 -- Apple Inc. has set the date for a media event to unveil the first redesign to its MacBook Pro laptop in five years: Oct. 18.", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "v39Dspkt4EE", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Shadow Animation in NativeScript | Tutorial", "Time Created": null, "Time Published": "2020-04-10T18:17:45Z", "Duration": null, "Description": "In this NativeScript tutorial, we're animating a shadow to make a button pop up when touched on both iOS and Android. Check out ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "nRZkvOtuoUg", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "Live Stream: Apple M1 for Developers", "Time Created": null, "Time Published": "2020-12-20T08:00:38Z", "Duration": null, "Description": "Come hang out as I test the Apple M1 Macs and do some software performance tests/ You can bring your suggestions, or just ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "N9TjpXxf_lw", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "How to Use iOS Large Titles | NativeScript Tutorial", "Time Created": null, "Time Published": "2019-08-28T01:07:16Z", "Duration": null, "Description": "Large title support was added in iOS 11 and since it's an iOS only feature, there is no reason for NativeScript to add it to their ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "vXy-FhGmDdM", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Tools Creator Nathanael Anderson", "Time Created": null, "Time Published": "2020-04-27T20:05:41Z", "Duration": null, "Description": "In this NativeScript chat, I talk to Nathanael Anderson, a long time NativeScript guru and the creator of many of the tools you know ...", "Category": null, "Like Count": null, "Dislike Count": null}
{"Video ID": "G_iPBdYdCyU", "Channel ID": "UCajiMK_CY9icRhLepS8_3ug", "Title": "NativeScript Community Spotlight - Nic Raboy", "Time Created": null, "Time Published": "2020-03-02T19:26:26Z", "Duration": null, "Description": "Continuing my chats with NativeScript community members, here's my chat with Nic Raboy. He is a meetup organizer, course ...", "Category": null, "Like Count": null, "Dislike Count": null}