Introduction
Welcome to the final session of PCA. In the previous session, you discovered and learnt the theoretical concepts of PCA. In this session, you will learn how to implement PCA in python on some real examples.
In this session, you will learn how to use PCA on a problem you have already encountered before – predicting telecom churn using logistic regression. You will now learn to implement PCA in tandem with logistic regression.
In this session
Let’s look at the broad flow of this session.
Prerequisites
There are no prerequisites for this session other than the knowledge of the previous sessions.
Guidelines for in-module questions
The in-video and in-content questions for this module are not graded. The graded questions are given in a separate segment labelled ‘Graded Questions’ at the end of the session. The questions in that segment will adhere to the following guidelines:
| First Attempt Marks | Second Attempt Marks | |
| Question with 2 Attempts | 10 | 5 |
| Question with 1 Attempt | 10 | 0 |