Neural networks are the main machine learning models that we will be looking at in this book. Their applications are countless, as are their application fields. These range from computer vision applications (where an object should be localized in an image), to finance (where neural networks are applied to detect frauds), passing trough trading, to reaching even the art field, where neural networks are used together with the adversarial training process to create models that are able to generate new and unseen kinds of art with astonishing results.

This chapter, which is perhaps the richest in terms of theory in this whole book, shows you how to define neural networks and how to make them learn. To begin, the mathematical formula for artificial neurons will be presented, and we will highlight why a neuron must have certain features to be able to...