Catalog · Matrix Methods in Data Analysis, Signal Processing, and Machine Learning Lecture 6 of 34 Lecture 6: Singular Value Decomposition (SVD) ← Previous Lecture 5: Positive Definite and Semidefinite Matrices Next → Lecture 7: Eckart-Young: The Closest Rank k Matrix to A ✓ Mark complete Materials Transcript (PDF) ↗ transcript