Handwritten digit recognition system trained on MNIST data. Taken from neuralnetworksanddeeplearning.com and updated to work with Python 3.6 This NN gives accuracy upto 95-96%. To get started, just clone or download the repo and run following commands:

import mnist_loader

training_data, validation_data, test_data = \

mnist_loader.load_data_wrapper()

import network

net = network.Network([784, 30, 10])

net.SGD(training_data, 30, 10, 3.0, test_data=test_data)

You can also change the parameters in the last two lines to change the number of hidden networks (30 in the example) and number of epochs, batch size and learning rate (30, 10 and 3.0 respectively) in the final line as you prefer. You also need to change the location of the files in network.py.