Linear applications and eigenvalues

Related lectures (28)

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

Covers fundamental linear algebra concepts like vector spaces and eigenvalues.

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

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.

Explores matrix operations, linear systems, solutions, and the span of vectors in linear algebra.

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

Introduces orthogonal sets and bases, discussing their properties and linear independence.

Covers the concept of 3D vector space, scalar product, bases, orthogonality, and projections.

Covers eigenvalues, eigenvectors, and diagonalization of matrices.

Explores orthogonality, dot product properties, vector norms, and angle definitions in vector spaces.