Lectures related to The Simplex Algorithm

Covers the concept of interesting subspaces related to matrices and the change of basis matrix.

Covers strategies for calculating determinants and their geometric interpretation in various dimensions.

Covers the simplex algorithm, pivoting, elementary row operations, and transformations to find matrix Q.

Covers the LU decomposition algorithm, transforming a matrix into L and U.

Introduces elementary row operations on matrices and their applications in solving systems of linear equations.

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

Explores matrix similarity, diagonalization, characteristic polynomials, eigenvalues, and eigenvectors in linear algebra.