Linear Applications in 3D: Rank Theorem

Related lectures (28)

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

Revisits bases of the image and kernel in linear algebra, focusing on linear transformations between finite-dimensional vector spaces.

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

Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.

Explores unique solutions, linear dependence, canonical bases, and linear maps 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 basics of linear algebra, including linear maps, bases, and matrix operations.

Covers the concepts of kernel and image of a linear application in linear algebra.

Explores injective and surjective linear transformations, kernel, image, and matrix operations.

Explores linear applications, matrices, ranks, kernels, and dimensions in linear algebra.