Handwritten digit recognition

Final project for the OOP course. It uses a fairy simple neural net, trained on MNIST dataset to recognize handwritten digits. User is able to create multi-layer neural network by specifying layers' type (Sigmoid or ReLU) and size, choosing cost function and hyperparameters' values. Created network can be tested then and if its accuracy is sufficient for the user, that person can save the model to a file and load it later to feed images into it and learn what digits they contain.