Kernel Methods: Machine Learning

This lecture covers kernel methods in machine learning, focusing on kernelized versions of linear regression, ridge regression, and support vector machines. It explains the concept of kernel functions, the kernel trick, and the application of kernel methods in regression tasks. The lecture also delves into the importance of model complexity, overfitting, and the regularization techniques used to prevent overfitting.