Lectures related to Matrix Eigenvalues and Eigenvectors

Covers the decomposition of matrices into triangular blocks and spectral decomposition.

Covers Canonical Correlation Analysis, a method to find relationships between two sets of variables.

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Covers the basics of linear algebra, including matrix operations and singular value decomposition.

Explores normal equations, pseudo-solutions, unique solutions, and symmetric matrices in linear algebra.

Explores eigenvalues, matrix trace, and similarity, highlighting their significance in matrix properties.