A neural network written with NumPy
Two distinctive features of this particular code is that
- you can vary the number of layers and output neurons and
- the training samples are completely vectorised.
This notebook will go through how the n-layer, m-output (n and m are varying integers) neural network works. This is a fully vectorised network, meaning that the use of for-loops is replaced with numpy vectors whenever possible to reduce the run-time.