November 2016
Beginner to intermediate
941 pages
21h 55m
English
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 ...