771: Gradient Boosting: XGBoost, LightGBM and CatBoost, with Kirill Eremenko
Update: 2024-04-02
Description
Kirill Eremenko joins Jon Krohn for another exclusive, in-depth teaser for a new course just released on the SuperDataScience platform, “Machine Learning Level 2”. Kirill walks listeners through why decision trees and random forests are fruitful for businesses, and he offers hands-on walkthroughs for the three leading gradient-boosting algorithms today: XGBoost, LightGBM, and CatBoost.
This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), and by Data Universe, the out-of-this-world data conference (https://datauniverse2024.com). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.
In this episode you will learn:
• All about decision trees [09:28 ]
• All about ensemble models [22:03 ]
• All about AdaBoost [38:46 ]
• All about gradient boosting [46:51 ]
• Gradient boosting for classification problems [1:01:26 ]
• All about XGBoost, LightGBM and CatBoost [1:04:12 ]
Additional materials: www.superdatascience.com/771
This episode is brought to you by Ready Tensor, where innovation meets reproducibility (https://www.readytensor.ai/), and by Data Universe, the out-of-this-world data conference (https://datauniverse2024.com). Interested in sponsoring a SuperDataScience Podcast episode? Visit passionfroot.me/superdatascience for sponsorship information.
In this episode you will learn:
• All about decision trees [09:28 ]
• All about ensemble models [22:03 ]
• All about AdaBoost [38:46 ]
• All about gradient boosting [46:51 ]
• Gradient boosting for classification problems [1:01:26 ]
• All about XGBoost, LightGBM and CatBoost [1:04:12 ]
Additional materials: www.superdatascience.com/771
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