Linear Mapping Basics

Related lectures (25)

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

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

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

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

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

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

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

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

Explores the Rank Theorem in linear algebra, covering matrix properties and determinants.

Explores matrix operations, rank determination, kernel dimensions, and basis concepts in linear algebra.