Linear Algebra: Systems of Equations

Related lectures (29)

Page 3 of 3

Covers the concept of basis, linear transformations, matrices, inverses, determinants, and bijective transformations.

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Explores linear applications, vector spaces, kernels, and invertibility in linear algebra.

Covers the concepts of kernel and image of a linear transformation and their relationship with the rank of the matrix.

Covers the Moore-Penrose pseudoinverse and its properties for arbitrary matrices.

Covers strategies for matrix operations and the concept of vector spaces.

Covers fundamental linear algebra concepts like vector spaces and eigenvalues.

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

Introduces linear algebra basics, including linear independence, injectivity, surjectivity, and bases in vector spaces.