Lectures related to Geometric Transformations in R2 and R3

Introduces orthogonal matrices, the least squares method, and their practical applications in linear algebra.

Covers linear applications, matrices, transformations, and the principle of superposition.

Explores matrix operations, rank determination, kernel dimensions, and basis concepts in linear algebra.

Covers vector spaces, bases, and decomposition of vectors in R³.

Explores linear applications, matrices properties, vector subspaces, and system resolution.

Covers kernels and images of linear transformations between vector spaces.

Explores normal equations, pseudo-solutions, unique solutions, and symmetric matrices in linear algebra.

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