In the last two chapters, we have presented some of the most basic and popular models for regression and classification tasks. In this chapter, we introduce a family of models based on neural networks. This family of models is the basis for the field of deep learning—an approach to machine learning behind some of the most exciting and recent advances in the field of artificial intelligence.
This chapter will give you enough knowledge to be able to use neural networks for predictive analytics; the point here is to present the fundamental concepts about these models and learn to train the most fundamental type of neural network—the multilayer perceptron (MLP).
First, we will cover the main concepts of neural networks when talking about the anatomy of an MLP; then we will discuss how these models learn to make predictions...
