Module 10- Theory 3: Advanced ML boosting techniques: XGboost, Catboost, LightGBM
861 بار بازدید -
9 ماه پیش
-
Relevant playlists:
Machine Learning Codes
Relevant playlists:
Machine Learning Codes and Concepts: • Machine Learning Codes and Concepts (...
Deep Learning Concepts, simply explained: • Deep Learning Concepts (Simply Explai...
Instructor: Pedram Jahangiry
All of the slides and notebooks used in this series are available on my GitHub page, so you can follow along and experiment with the code on your own.
https://github.com/PJalgotrader
Lecture Outline:
https://www.seevid.ir/fa/w/0YRg9DVl0AI Intro
https://www.seevid.ir/fa/w/0YRg9DVl0AI Decision trees fundamental questions
https://www.seevid.ir/fa/w/0YRg9DVl0AI 1- What features to start with and where to put the split?
https://www.seevid.ir/fa/w/0YRg9DVl0AI 2- How to split the samples? presorted-histogram, GOSS and Greedy methods
https://www.seevid.ir/fa/w/0YRg9DVl0AI 3- How to grow a tree? Depth-wise, level-wise, leaf-wise and symmetric
https://www.seevid.ir/fa/w/0YRg9DVl0AI 4- How to combine the trees? bagging vs boosting
https://www.seevid.ir/fa/w/0YRg9DVl0AI Evolution of XGboost
https://www.seevid.ir/fa/w/0YRg9DVl0AI LightGBM and CatBoost
https://www.seevid.ir/fa/w/0YRg9DVl0AI comparing XGBoost, LightGBM and CatBoost
9 ماه پیش
در تاریخ 1402/10/02 منتشر شده
است.
861
بـار بازدید شده