Linear Applications Overview

Related lectures (26)

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Explains how to calculate the dimension of a kernel of a matrix transpose.

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

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

Explores subspaces in linear algebra and transformations, including kernels and images of linear transformations.

Explores linear applications, matrices properties, vector subspaces, and system resolution.

Covers fundamental linear algebra concepts like vector spaces and eigenvalues.

Explores linear applications in 3D, emphasizing images, kernels, and solution uniqueness in systems.

Introduces fundamental concepts in linear algebra, such as vector spaces and eigenvalues.

Covers bases, transformations, and matrix decompositions in linear algebra.

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