ML Foundations V - Unsupervised and Non-Parametric Methods

Explore fundamental unsupervised learning and non-parametric methods in this comprehensive machine learning lecture covering distance functions, parametric versus non-parametric approaches, and k-nearest neighbor algorithms. Delve into clustering techniques including k-means and hierarchical clustering, learn evaluation methods for unsupervised learning approaches, and discover rule learning concepts through itemset mining and the A Priori algorithm. Master association rule mining techniques to uncover patterns in data, gaining essential skills for analyzing unlabeled datasets and extracting meaningful insights without supervised guidance.