Lectures related to Linear Algebra Review

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Explores symmetric matrices, their diagonalization, and properties like eigenvalues and eigenvectors.

Explores the Cholesky factorization method for symmetric positive definite matrices.

Covers the decomposition of symmetric matrices into eigenvalues and eigenvectors.

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

Covers essential linear algebra concepts for convex optimization, including vector norms, eigenvalue decomposition, and matrix properties.