Decision Trees 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-classification-trees-in-python-from-start-to-finish/

This webinar was recorded 20200528 at 11:00am (New York time).

NOTE: This StatQuest assumes are already familiar with:
Decision Trees: https://youtu.be/7VeUPuFGJHk
Cross Validation: https://youtu.be/fSytzGwwBVw
Confusion Matrices: https://youtu.be/Kdsp6soqA7o
Cost Complexity Pruning: https://youtu.be/D0efHEJsfHo
Bias and Variance and Overfitting: https://youtu.be/EuBBz3bI-aA

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

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0:00 Awesome song and introduction
5:23 Import Modules
7:40 Import Data
11:18 Missing Data Part 1: Identifying
15:57 Missing Data Part 2: Dealing with it
21:16 Format Data Part 1: X and y
23:33 Format Data Part 2: One-Hot Encoding
37:29 Build Preliminary Tree
46:31 Pruning Part 1: Visualize Alpha
51:22 Pruning Part 2: Cross Validation
56:46 Build and Draw Final Tree

#StatQuest #ML #ClassificationTrees

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