Summary
This chapter might be hard to process if this was your first encounter with deep learning and neural networks. Going over the materials a couple of times could help, but it won't be enough to understand the topic fully. Entire books have been written on deep learning, and even on small subsets of deep learning. Hence, covering everything in a single chapter isn't possible.
Still, you should have the basic theory behind the concepts of neurons, layers, and activation functions, and you can always learn more on your own. The following chapter, Chapter 7, Neural Network Classifier with TPOT, will show you how to connect neural networks and pipeline optimization, so you can build state-of-the-art models in a completely automated fashion.
As always, please feel free to explore the theory and practice of deep learning and neural networks on your own. It is definitely a field of study worth exploring further.
