PCA: Interactive class

This lecture on Principal Component Analysis (PCA) covers key concepts such as reducing data dimensionality and extracting features. It includes interactive exercises on dataset reduction, preprocessing for classification, and interpreting PCA projections. The instructor emphasizes the importance of choosing the optimal number of eigenvectors to minimize information loss.