Lectures related to Linear Applications and Eigenvectors

Covers eigenvalues, eigenvectors, and diagonalization of matrices.

Covers the properties and operations of vector spaces, including addition and scalar multiplication.

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Covers matrix operations, scalar product, orthogonality, and bases in vector spaces.

Covers the properties of vectors, including commutativity, distributivity, and linearity.

Covers the concept of orthogonal complement in Rn and related propositions and theorems.