This chapter is the most theoretical of the six chapters in *Neural Networks
and Deep Learning*. It derives the equations for gradient descent and provides
strong mathematical intuitions for why they actually make sense. (These types
of intuitions were why we decided to read *Neural Networks and Deep Learning*
as a group.) Finally, the chapter contains some code for implementing gradient
descent in the neural network we coded from scratch in the first chapter.