Episode 4 - Ensemble models. Bagging and boosting

What this episode covers

In this episode, I'm going to talk about ensemble models, particularly bagging and boosting. Bagging is very useful for reducing variance, boosting is used for reducing bias. The most common bagging algorithm is Random Forest, the most common boosting algorithm is Gradient Boosting, whose most common implementations are XGBoost, LightGBM and CatBoost. Home Page: https://www.yourdatateacher.com

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Frequently Asked Questions

How long is this episode of Your Data Teacher Podcast?

This episode is 11 minutes long.

When was this Your Data Teacher Podcast episode published?

This episode was published on June 10, 2021.

What is this episode about?

In this episode, I'm going to talk about ensemble models, particularly bagging and boosting. Bagging is very useful for reducing variance, boosting is used for reducing bias. The most common bagging algorithm is Random Forest, the most common...

Can I download this Your Data Teacher Podcast episode?

Yes, you can download this episode by clicking the download button on the episode player, or subscribe to the podcast in your preferred podcast app for automatic downloads.