Update README.md

README.md

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 # AlphaNum Dataset
 
 ## Dataset Summary
-The AlphaNum dataset, created by Louis Rädisch, is a collection of handwritten grayscale characters and digits of the size 28x28 intended for the use in Optical Character Recognition (OCR) tasks. This dataset is a compilation from various sources and includes labels from 0-35, where 0-25 represent the letters A-Z and 26-35 represent the digits 0-9. The images from the MNIST dataset included have been color inverted.
-To bring together the different datasets, vision transformer Models have been fine tuned to further increase the accuracy of the data. For instance the  "A-Z handwritten alphabets" had no seperation between big and small letters. 
+The AlphaNum dataset, curated by Louis Rädisch, is a comprehensive collection of grayscale, handwritten characters and digits, each with dimensions of 28x28 pixels. The primary aim of this dataset is to aid Optical Character Recognition (OCR) tasks. The dataset encompasses labels ranging from 0-35, wherein labels 0-25 correspond to the English alphabets (A-Z) and labels 26-35 correspond to the digits (0-9). Interestingly, the images derived from the MNIST dataset have been color inverted to maintain consistency with the rest of the data.
 
-## Sources:
-1) [handwritting_characters_database](https://github.com/sueiras/handwritting_characters_database) 
-2) [mnist](https://huggingface.co/datasets/mnist)
-3) [az-handwritten-alphabets-in-csv-format](https://www.kaggle.com/datasets/sachinpatel21/az-handwritten-alphabets-in-csv-format)
+To harmonize the data from diverse sources, Vision Transformer Models have been fine-tuned, enhancing the accuracy of the dataset. For instance, the 'A-Z handwritten alphabets' dataset originally did not differentiate between upper and lower case letters, an issue rectified in this new compilation.
 
+## Sources:
+1) [Handwriting Characters Database](https://github.com/sueiras/handwritting_characters_database) 
+2) [MNIST](https://huggingface.co/datasets/mnist)
+3) [AZ Handwritten Alphabets in CSV format](https://www.kaggle.com/datasets/sachinpatel21/az-handwritten-alphabets-in-csv-format)
 
+The dataset files have been scaled down to 24x24 pixels and recolored from white-on-black to black-on-white to ensure uniformity.
 
 ## Dataset Structure
 ### Data Instances
-A data instance in this dataset is an image of a handwritten character or digit along with its corresponding label.
+A single data instance in this dataset comprises an image of a handwritten character or digit, accompanied by its corresponding label.
 
 ### Data Fields
-1) 'image': The image of the handwritten character or digit.
-2) 'label': The label for the character or digit in the image. (0-25 for A-Z, 26-35 for 0-9)
+1) 'image': This field contains the image of the handwritten character or digit.
+2) 'label': This field provides the label corresponding to the character or digit in the image. (0-25 are assigned to A-Z, 26-35 to 0-9)
 
 ### Data Splits
-The dataset is divided into training and test sets.
+The dataset is bifurcated into training and test subsets to facilitate the building and evaluation of models.
 
 ## Dataset Use
-The AlphaNum dataset is suitable for tasks related to text recognition, document processing, and machine learning, particularly in the development and improvement of OCR models.
+The AlphaNum dataset is apt for tasks associated with text recognition, document processing, and machine learning. It is particularly beneficial for constructing, fine-tuning, and enhancing OCR models.