In this project, I implemented two fundamental types of neural network models, all in plain numpy: a feed-forward fully-connected network and a convolutional neural network. This includes defining Activation functions (Linear, ReLU, Softmax), Cross Entropy Loss function, Layers (Fully-connected, Conv2D), and the stochastic gradient descent with backpropagation algorithm of the network. You can find my code here.