Lectures related to Matrix Algebra: Properties and Operations

Covers the Gram-Schmidt algorithm for orthonormal bases in vector spaces.

Covers the process of finding a base from a system of generators in linear algebra.

Explores subspaces in linear algebra and transformations, including kernels and images of linear transformations.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.

Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.

Covers the definition and examples of vector spaces, including subspaces and linear transformations.