Hands-on exercise

In this hands-on exercise, we will build a Jupyter Notebook environment on your local machine and build and train an ML model in your local environment. The goal of the exercise is to get some familiarity with the installation process of setting up a local data science environment, and learn how to analyze the data, prepare the data, and train an ML model using one of the algorithms we covered in the preceding sections. First, let's take a look at the problem statement.

Problem statement

Before we start, let's first review the business problem that we need to solve. A retail bank has been experiencing a high customer churn rate for its retail banking business. To proactively implement preventive measures to reduce potential churn, the bank needs to know who the potential churners are, so the bank can target those customers with incentives directly to prevent them from leaving. From a business perspective, it is far more expensive to acquire a new customer...