Neural Network from scratch

This is my implementation of a feedforward neural network with ReLU activation functions. I loosely followed the workflow outlined in the book https://nnfs.io.

Project organization

The project has four main files:

• NeuralNetwork.py includes all the necessary classes for performing a forward and backward pass in the network.
• Optimizer.py contains the stochastic gradient descent optimizer implementation and the Trainer class responsible for training.
• Evaluation.py includes the class that calculates the model's Accuracy.
• main.py holds the code that trains and tests the neural network on a classification problem using spiral data.

Requirements are specified in requirements.txt.