An Actual Application for the MNIST Digits Classifier

Have you ever thought to yourself "I just made a great MNIST classifier! While the handwritten digits dataset is a great, clean way to get into machine learning (on the classification side, anyway), it is rightly dubbed the "Hello World" of the field. You can use it to make a sensible ML pipeline and learn how to implement different kinds of models, but it doesn't have much use past that… until now. One of my first posts here used some basic python data structures and logic to solve Sudoku puzzles about twice as fast as you could blink, but I had to manually enter the numbers into the arrays to prepare the solver. In this post, I'd like to get into how to use some image processing tools and a convolutional neural net to function for optical character recognition (OCR).