In the previous chapters, we presented an implementation of a neural network made of layers and neurons (i.e., instances of NeuronLayer and Neuron). Although instructive, that implementation does not reflect classical ways of implementing a neural network. A layer can be expressed as a matrix of weights and a vector of biases. This is how most libraries that build neural networks (e.g., TensorFlow and PyTorch) actually operate.
This chapter lays out a small library to build and manipulate matrices. This chapter is an important foundation for the subsequent chapter, which is about ...
