Lectures related to Linear Algebra: Matrices and Linear Applications

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.

Explores geometric transformations in R2 and R3, including linear transformations, projections, matrices, and trace properties.

Explores vector spaces, subspaces, bases, and linear combinations in R² and R³, including free and linked families.

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

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

Explains linear independence, basis, and matrix rank with examples and exercises.

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.