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Related lectures (25)

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Covers matrix equations as linear combinations, vector spaces, and geometric interpretations.

Explores vector spaces, subspaces, bases, and linear combinations in R² and R³, including free and linked families.

Explores linear dependence and independence of vectors, including subspaces generation and corollaries.

Introduces the concept of basis and canonical basis in linear algebra, essential for vector space representation.

Explores linear dependence and independence of vectors in geometric spaces.

Covers the diagonalization of matrices using eigenvectors and eigenvalues.

Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.

Explores free generating families in linear algebra, discussing subspaces, stability, and linear dependency relations.

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

Covers the properties and criteria of linear dependence and independence in a vector space.