NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: https://statquest.gumroad.com/l/uroxo
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
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
https://statquest.org/statquest-store/
...or just donating to StatQuest!
https://www.paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer
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