Lectures related to Orthogonal Projection: Spectral Decomposition

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

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

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.