Chapter 7. Supervised Learning: Predicting Customer Churn

Note

Learning Objectives

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

• Perform classification tasks using logistic regression

• Implement the most widely used data science pipeline (OSEMN)

• Perform data exploration to understand the relationship between the target and explanatory variables.

• Select the important features for building your churn model.

• Perform logistic regression as a baseline model to predict customer churn.

Note

This chapter covers classification algorithms such as logistic regression and explains how to implement the OSEMN pipeline.