This lecture covers unsupervised learning, focusing on Principal Component Analysis (PCA) with motivating examples such as mapping human genome and people in Europe. It also discusses the Singular Value Decomposition (SVD) and the Young-Eckart theorem.
This video is available exclusively on Mediaspace for a restricted audience. Please log in to MediaSpace to access it if you have the necessary permissions.
Watch on Mediaspace