Lectures related to Linear applications and eigenvalues

Covers the theory and examples of diagonalizing matrices, focusing on eigenvalues, eigenvectors, and linear independence.

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

Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.

Introduces orthogonality between vectors, angles, and orthogonal complement properties in vector spaces.

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

Explores orthogonality, norms, and distances in vector spaces for solving linear systems.

Explores polynomial operations, properties, and subspaces in vector spaces.

Explores the properties and applications of the dot product in vector spaces.