771: Gradient Boosting: XGBoost, LightGBM and CatBoost — with Kirill Eremenko

#GradientBoosting #XGBoost #LightGBM #CatBoost Kirill Eremenko joins @JonKrohnLearns 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 https://passionfroot.me/superdatascience for sponsorship information. In this episode you will learn: • [00:00:00] Introduction • [00:07:58] All about decision trees • [00:20:33] All about ensemble models • [00:37:17] All about AdaBoost • [00:45:21] All about gradient boosting • [00:59:56] Gradient boosting for classification problems • [01:04:09] Advantages of XGBoost • [01:18:00] LightGBM • [01:33:27] CatBoost Additional materials: https://www.superdatascience.com/771