DigitClassifier

A neural network with three hidden layers, and a self-implemented back propagation, to identify handwritten digits from the MNIST database with ~94% accuracy, and a best of 95% accuracy.

Getting Started

• Download the binary files of the test data from the MNIST database
• Run python mnistToText.py on both the training set and validation set to convert both files into text files.
• Run python app.py to train the neural network on the training set, and then test its accuracy on the validation set.