Cross Validation

Learn how to use K-Fold cross validation to perform more rigorous testing.


  • Learn how cross-validation lets us more accurately understand model performance.
  • Learn the difference between holdout and k-fold cross validation.
  • Learn how to perform cross-valudation in scikit-learn.

Mission Outline

1. Introduction
2. Holdout Validation
3. K-Fold Cross Validation
4. First iteration
5. Function for training models
6. Performing K-Fold Cross Validation Using Scikit-Learn
7. Exploring Different K Values
8. Bias-Variance Tradeoff
9. Next steps
10. Takeaways

Course Info:

Machine Learning Fundamentals


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

This course requires a premium subscription. This course includes five paid missions and one guided project.  It is the 17th course in the Data Scientist in Python path.


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