In the previous chapter, we covered linear neural networks, which have proven to be effective for problems such as regression and so are widely used in the industry. However, we also saw that they have their limitations and are unable to work effectively on higher-dimensional problems.
In this chapter, we will take an in-depth look at the multilayer perceptron (MLP), a type of feedforward neural network (FNN). We will start by taking a look at how biological neurons process information, then we will move onto mathematical models of biological neurons. The artificial neural networks (ANNs) we will study in this book are made up of mathematical models of biological neurons (we will learn more about this shortly). Once we have built a foundation, we will move on to understanding how MLPs—which are the FNNs—work and their involvement with...
