Lecture 11: K-means clustering (unsupervised learning) – Machine Learning for Engineers

This video is part of the "Artificial Intelligence and Machine Learning for Engineers" course offered at the University of California, Los Angeles (UCLA). This course introduces ML/AI theory and applications that are relevant to engineering, with a focus on practical machine learning for civil engineering. In this lecture, we focus on the k-means clustering algorithm. We discuss how to determine the distortion of the clusters and how to determine the optimal number of clusters k using the Elbow method.