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

linear-regression-for-machine-learning

Course Info:

Intermediate

The median completion time for this course is 7.23 hours. View Details

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.

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