Lectures related to Singular Value Decomposition

Delves into singular value decomposition and its applications in linear algebra.

Explores the diagonalization of symmetric matrices through orthogonal decomposition and the spectral theorem.

Introduces Singular Value Decomposition (SVD) in linear algebra, covering matrix factorization and properties with practical examples.

Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.