Linear Algebra: Matrix Representation

Related lectures (25)

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Explains orthogonal families, bases, and projections in vector spaces.

Covers landmarks, coordinate systems, frames, and terminology in coordinates, emphasizing geometric angles and orthogonal vectors.

Covers the theorems related to orthogonal projection and orthonormal bases.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.

Covers the basics of linear algebra, including linear maps, bases, and matrix operations.

Explores the canonical basis in linear algebra, focusing on matrix representation, diagonalizability, and characteristic polynomials.

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

Explains linear independence, basis, and matrix rank with examples and exercises.