Hands-On Unsupervised Learning Using Python

Chapter 1. Unsupervised Learning in the Machine Learning Ecosystem

Most of human and animal learning is unsupervised learning. If intelligence was a cake, unsupervised learning would be the cake, supervised learning would be the icing on the cake, and reinforcement learning would be the cherry on the cake. We know how to make the icing and the cherry, but we don’t know how to make the cake. We need to solve the unsupervised learning problem before we can even think of getting to true AI.

Yann LeCun

In this chapter, we will explore the difference between a rules-based system and machine learning, the difference between supervised learning and unsupervised learning, and the relative strengths and weaknesses of each.

We will also cover many popular supervised learning algorithms and unsupervised learning algorithms and briefly examine how semisupervised learning and reinforcement learning fit into the mix.

Basic Machine Learning Terminology

Before we delve into the different types of machine learning, let’s take a look at a simple and commonly used machine learning example to help make the concepts we introduce tangible: the email spam filter. We need to build a simple program that takes in emails and correctly classifies them as either “spam” or “not spam.” This is a straightforward classification problem.

Here’s a bit of machine learning terminology as a refresher: the input variables into this problem are the text of the emails. These input variables are also known as features ...