Linear Maps and Matrices

Related lectures (27)

Page 1 of 3

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

Explains kernel, image, and linear maps, illustrating concepts with examples.

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

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

Explores matrix representations of linear maps and their invariance, using examples and special cases.

Explores properties of linear applications, including symmetric matrices and linearity in analysis.

Covers the properties and operations of vector spaces, including addition and scalar multiplication.

Covers the determination of matrices associated with linear transformations and explores the kernel and image concepts.

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

Covers linear algebra basics, including matrices, change of basis, and invertible matrices.