Linear Transformations: Matrices and Applications

Related lectures (25)

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Covers the properties of vectors, including commutativity, distributivity, and linearity.

Covers linear independence, bases, and coordinate systems with examples and theorems.

Explores changing bases in linear algebra in 3 dimensions, focusing on matrix transformations and vector representations.

Covers the concept of expressing vectors in proper bases and the importance of diagonalization of matrices.

Explains orthogonal projection in linear algebra, focusing on transforming non-orthogonal bases into orthogonal ones.

Explores linear algebra fundamentals, including key definitions, theorems, and practical applications in mathematics and technology.

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

Explores linear dependence and independence of vectors in geometric spaces.

Covers parametric to Cartesian representation, linear independence, bases, linear transformations, and linear applications.

Explores isometries in Euclidean spaces, including translations, rotations, and linear symmetries, with a focus on matrices.