This chapter revises the implementation of our neural network. In this revision, our network will use matrices to compute the forward and backward propagation algorithms. Overall, our matrix-based implementation is composed of two classes, NMLayer and NMNetwork. Since most of the computation is delegated to the matrix library we defined in the previous chapter, our new version of the neural network is rather light in terms of code.
7.1 Defining a Matrix-Based Layer
A neural network is composed of layers. We describe a layer as an instance of the NMLayer class
, defined ...
