Lectures related to Linear Algebra: Reduction of Linear Application

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

Explores the properties and examples of diagonalizable matrices, emphasizing the relationship between eigenvectors and eigenvalues.

Covers the reduction of a linear transformation in a 2-dimensional space to find a simpler matrix representation.

Explores the diagonalization of matrices through eigenvalues and eigenvectors, emphasizing the importance of bases and subspaces.

Covers the basics of linear algebra, including linear maps, bases, and matrix operations.

Offers a quick review of key linear algebra concepts essential for further topics.

Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.