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Lecture
Singular Value Decomposition: Theory and Applications
Description
This lecture covers the theory and applications of Singular Value Decomposition (SVD). It explains the concept of singular values, eigenvectors, and the decomposition of a matrix into U, Σ, and V matrices. The instructor demonstrates how to obtain U and V matrices and discusses the uniqueness of the SVD decomposition.
Official source
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