Ensemble Methods in Machine Learning

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Why Ensemble Methods in Machine Learning?

Models are great on their own but you can make them better by combining them together! Ensemble methods are techniques in machine learning that help you do this.

Take-Away Skills:

Learn how to bag models to build random forests, boost models using adaptive and gradient boosting, and stack models for improved performance!

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  1. 1
    Learn about ensembling methods in machine learning like bagging, boosting and stacking!
  2. 2
    Learn about bagging, random forests and how to implement them using scikit-learn!
  3. 3
    Learning about boosting machine learning models!

What you'll create

Portfolio projects that showcase your new skills

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How you'll master it

Stress-test your knowledge with quizzes that help commit syntax to memory

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— Madelyn, Pinterest

I know from first-hand experience that you can go in knowing zero, nothing, and just get a grasp on everything as you go and start building right away.

Course Description

Learn about ensembling methods in machine learning!

Details

Earn a certificate of completion
3 hours to complete in total
Intermediate

1 informational, 1 article

Learn about bagging, random forests and how to implement them using scikit-learn!

1 lesson, 1 article, 1 informational