Lectures related to Linear Algebra Basics: Vector Spaces, Transformations, Eigenvalues

Covers linear transformations between polynomial spaces and explores examples of linear independence and bases.

Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.

Covers the decomposition of a matrix into its eigenvalues and eigenvectors, the orthogonality of eigenvectors, and the normalization of vectors.