Support Vector Machines use kernel functions to do all the hard work and this StatQuest dives deep into one of the most popular: The Radial (RBF) Kernel. We talk about the parameter values, how they calculate high-dimensional coordinates and then we'll figure out, step-by-step, how the Radial Kernel works in infinite dimensions. NOTE: This StatQuest assumes you already know about... Support Vector Machines: Cross Validation: The Polynomial Kernel: ALSO NOTE: This StatQuest is based on... 1) The description of Kernel Functions, and associated concepts on pages 352 to 353 of the Introduction to Statistical Learning in R: 2) The derivation of the of the infinite dot product is based on Matthew Bernstein's notes: ~matthewb/pages/notes/pdf/svms/ For a complete index of all the StatQuest videos, check out: If you'd like to support StatQuest, please consider... Patreon: ...or... YouTube Membership: ...buying one of my books, a study guide, a t-shirt or hoodie, or a song from the StatQuest store... ...or just donating to StatQuest! Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: #statquest #SVM #RBF