Linear Algebra: Matrix Representation

Related lectures (25)

Page 1 of 3

Covers matrices, linear applications, vector spaces, and bijective functions.

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

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

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

Explores vector space operations, linear transformations, matrix representation, and linear applications.

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.

Explores the scalar product of vectors, including properties and calculation methods.

Covers fundamental concepts in linear algebra, including linear equations, matrix operations, determinants, and vector spaces.

Covers the basics of linear mapping and coordinate systems.

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.