MISSION 239

Processing and Transforming Features

Learn how to clean and prepare features for linear regression.

Objectives

  • Learn to transform the training set for a machine learning model.
  • Learn the basics of feature engineering.
  • Learn how to deal with missing data.

Mission Outline

1. Introduction
2. Categorical Features
3. Dummy Coding
4. Transforming Improper Numerical Features
5. Missing Values
6. Imputing Missing Values
7. Next Steps
8. Takeaways

Course Info:

Linear Regression for Machine Learning

Intermediate

The average completion time for this course is 10-hours.

This course requires a premium subscription and includes five missions and one guided project.  It is the 21st course in the Data Scientist in Python path.

START LEARNING FREE

Take a Look Inside

Share On Facebook
Share On Twitter
Share On Linkedin
Share On Reddit