Support Vector Machines Part 1 (of 3): Main Ideas

Support Vector Machines are one of the most mysterious methods in Machine Learning. This StatQuest sweeps away the mystery to let know how they work. Part 2: The Polynomial Kernel: Part 3: The Radial (RBF) Kernel: NOTE: This StatQuest assumes you already know The bias, variance tradeoff: Cross Validation: ALSO NOTE: This StatQuest is based on description of Support Vector Machines, and associated concepts, found on pages 337 to 354 of the Introduction to Statistical Learning in R: I also found this blogpost helpful for understanding the Kernel Trick: For a complete index of all the StatQuest videos, check out: If you d like to support StatQuest, please Buying