Lectures related to Matrix Factorization: LU Decomposition

Covers the concept of inverse matrices and systems resolution, including the conditions for matrix invertibility and the Gauss-Jordan algorithm.

Explains Singular Value Decomposition, focusing on orthogonal vectors and matrix decomposition.

Covers LU factorization, determinants, subspaces, and matrix products.

Covers the Jacobi method, Givens rotation, QR decomposition, and diagonalization techniques in computational physics.

Explores the link between linear systems and optimization through elimination and LU decomposition.

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