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+ ## My Notes 📓
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+ This repository contains my lecture notes from graduate school on following topics 👇🏼
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+ - Data Science: 8 cheatsheets
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+ - Machine Learning (follows [Tom Mitchell's book](http://www.cs.cmu.edu/~tom/mlbook.html)): 25 pages of notes
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+ - Statistics: 9 cheatsheets
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+ - Deep Learning: 12 cheatsheets, will upload more
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+ - Image Processing (follows [digital image processing book](https://www.amazon.fr/Digital-Image-Processing-Rafael-Gonzalez/dp/013168728X)): 21 cheatsheets
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+ - Data Structures and Algorithms (follows [this book by Goodrich](https://www.wiley.com/en-us/Data+Structures+and+Algorithms+in+Python-p-9781118549582)): 26 cheatsheets
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+ ✨ *Some notes* ✨
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+ - Most of these notes aren't intended to teach a topic from scratch but are rather notes that I took and compiled during my midterm & finals, might help you remember things, study for exams, and prepare for job interviews.
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+ - There might be very small Turkish notes in few of the pages, you can ignore them.
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+ - I will upload more notes as I find or create them. Will soon compile my Hugging Face cheatsheets so stay tuned!
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