Linear algebra

Related lectures (24)

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Explains how to find free variables in matrix equations and analyze characteristic polynomials.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.

Covers the diagonalization of matrices using eigenvectors and eigenvalues.

Provides an overview of symmetric matrices, quadratic forms, and their applications in linear algebra and analysis.

Covers linear equations, vectors, and matrices, exploring their fundamental concepts and applications.

Covers the diagonalization of linear transformations in R^3, exploring properties and examples.

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

Explores the fundamentals of Singular Value Decomposition, including orthonormal bases and practical applications.

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

Covers linear applications, diagonalizable matrices, eigenvectors, and orthogonal subspaces in R^n.