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Related lectures (29)

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Explores algebraic and geometric multiplicities of eigenvalues in linear algebra.

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

Explains methods for finding eigenvalues in linear algebra through examples.

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

Explores basis transformation, eigenvalues, and linear operators in inner product spaces, emphasizing their significance in Quantum Mechanics.

Explains the step-by-step process of diagonalization for linear transformations on finite-dimensional vector spaces.

Covers kernels and images of linear transformations between vector spaces, illustrating properties and providing proofs.

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

Covers eigenvectors, eigenvalues, and their significance in linear applications.