Chapter 1. Unsupervised Machine Learning

In this chapter, you will learn how to apply unsupervised learning techniques to identify patterns and structure within datasets.

Unsupervised learning techniques are a valuable set of tools for exploratory analysis. They bring out patterns and structure within datasets, which yield information that may be informative in itself or serve as a guide to further analysis. It's critical to have a solid set of unsupervised learning tools that you can apply to help break up unfamiliar or complex datasets into actionable information.

We'll begin by reviewing Principal Component Analysis (PCA), a fundamental data manipulation technique with a range of dimensionality reduction applications. Next, we will discuss ...

Get Python: Real World Machine Learning now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.