7. Eckart-Young: The Closest Rank k Matrix to A

MIT Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: YouTube Playlist: In this lecture, Professor Strang reviews Principal Component Analysis (PCA), which is a major tool in understanding a matrix of data. In particular, he focuses on the Eckart-Young low rank approximation theorem. License: Creative Commons BY-NC-SA More information at More courses at