Geometric Transformations in R2 and R3

Related lectures (28)

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Covers determining vector spaces, calculating kernels and images, defining bases, and discussing subspaces and vector spaces.

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

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Introduces orthogonal bases, projection onto subspaces, and the Gram-Schmidt process in linear algebra.

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

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

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

Covers the properties and operations of vector spaces, including addition and scalar multiplication.

Covers linear maps, matrices, and applications, including exercises on bases and invertibility.

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