Kernel Methods: Advanced Machine Learning

This lecture on advanced machine learning focuses on kernel methods, covering topics such as kernels, unsupervised learning, kernel PCA, kernel CCA, and classification algorithms. The instructor explains the key idea behind kernels, different types of kernels like Gaussian and polynomial kernels, and their applications in clustering, classification, and regression. The lecture also delves into finding non-linear manifolds using spectral decomposition, the computational steps and costs associated with various algorithms, and the use of Markov-based techniques in reinforcement learning. Additionally, the lecture provides insights into exam preparation, including theory, exercises, and comparisons between different algorithms.