Machine Learning - 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.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