Questions about Ensemble Methods frequently appear in data science interviews. In this video, I’ll go over various examples of ensemble learning, the advantages of boosting and bagging, how to explain stacking, and more!
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Contents of this video:
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00:00 Introduction
00:38 Ensemble Methods
01:40 Bagging (Bootstrap Aggregation)
03:00 Example: Random Forest
03:44 Boosting
05:14 Example: Gradient-Boosted Trees
05:47 Bagging vs. Boosting
06:40 Stacking
07:08 Two-Level Ensemble
07:44 Pros and Cons
