Machine Learning - Support Vector Machines in Python from Start to Finish.

NOTE: You can support StatQuest by purchasing the Jupyter Notebook and Python code seen in this video here: http://statquest.gumroad.com/l/iulnea This webinar was recorded 20200609 at 11:00am (New York Time) NOTE: This StatQuest assumes that you are already familiar with: Support Vector Machines: https://youtu.be/efR1C6CvhmE The Radial Basis Function: https://youtu.be/Qc5IyLW_hns 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 4:16 Import Modules 6:36 Import Data 11:27 Missing Data Part 1: Identifying 16:57 Missing Data Part 2: Dealing with it 21:04 Downsampling the data 24:35 Format Data Part 1: X and y 26:35 Format Data Part 2: One-Hot Encoding 31:25 Format Data Part 3: Centering and Scaling 32:45 Build a Preliminary SVM 34:55 Optimize Parameters with Cross Validation (GridSearchCV) 37:58 Build and Draw Final SVM #StatQuest #ML #SVM