Introduction

In the previous chapter, we learned about what clustering problems are and saw several algorithms, such as k-means, that can automatically group data points on their own. In this chapter, we will learn about neural networks and deep learning networks.

The difference between neural networks and deep learning networks is the complexity and depth of the networks. Traditionally, neural networks have only one hidden layer, while deep learning networks have more than that.

Although we will use neural networks and deep learning for supervised learning, note that neural networks can also model unsupervised learning techniques. This kind of model was actually quite popular in the 1980s, but because the computation power required was limited at the time, it's only recently that this model has been widely adopted. With the democratization of Graphics Processing Units (GPUs) and cloud computing, we now have access to a tremendous amount of computation power. This...