Chapter 3

Unsupervised Learning: Customer Segmentation

Learning Objectives

By the end of this chapter, you will be able to:

  • Describe the advantages of using unsupervised learning techniques (clustering) over more traditional segmentation techniques
  • Perform the preprocessing steps for preparing data for clustering
  • Use k-means clustering to perform customer segmentation
  • Determine the properties of groups created using clustering

This chapter covers various customer segmentation methods, deals with the concepts of similarity and data standardization, and explains k-means clustering.

Introduction

In the previous chapter, we saw how to build plots using the built-in function of pandas, and learned how to estimate the mean, median, and other ...

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