Lectures related to Diagonalization of Symmetric Matrices

Explores the diagonalization of symmetric matrices using eigenvectors and eigenvalues, emphasizing orthogonality and real eigenvalues.

Covers the properties of symmetric matrices, orthogonal matrices, and eigenvalues.

Explores spectral decomposition of symmetric matrices and Singular Value Decomposition (SVD) for matrix decomposition.

Explores the Spectral Theorem, emphasizing the Min-Max Criterion for symmetric matrices and the properties of positive definite matrices.

Explores stationary points, saddle points, symmetric matrices, and orthogonal properties in optimization.