XGBoost in Python from Start to Finish

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: https://statquest.org/product/jupyter-notebook-xgboost-in-python/

NOTE: This StatQuest assumes that you are already familiar with:
XGBoost for Regression: https://youtu.be/OtD8wVaFm6E
XGBoost for Classification: https://youtu.be/8b1JEDvenQU
XGBoost: Crazy Cool Optimizations: https://youtu.be/oRrKeUCEbq8
Regularization: https://youtu.be/Q81RR3yKn30
Cross Validation: https://youtu.be/fSytzGwwBVw
Confusion Matrices: https://youtu.be/Kdsp6soqA7o

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https://statquest.org/video-index/

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0:00 Awesome song and introduction
2:56 Import Modules
4:34 Import Data
13:43 Missing Data Part 1: Identifying
18:37 Missing Data Part 2: Dealing with it
24:03 Format Data Part 1: X and y
25:55 Format Data Part 2: One-Hot Encoding
33:25 XGBoost - Missing Data and One-Hot Encoding
36:43 Build a Preliminary XGBoost Model
45:01 Optimize Parameters with Cross Validation (GridSearchCV)
49:44 Build and Draw Final XGBoost Model

#StatQuest #ML #XGBoost

Видео XGBoost in Python from Start to Finish канала StatQuest with Josh Starmer