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Related lectures (29)

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Introduces vector spaces, bases, and the Hilbert space, highlighting the practical implications of defining a basis in a vector space.

Covers orthogonal vectors, unit vectors, and the Pythagorean theorem in R^m.

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

Explores the properties and applications of the dot product in vector spaces.

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

Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.

Introduces abstract concepts in linear algebra, focusing on operations with vectors and matrices.

Covers matrix operations, scalar product, orthogonality, and bases in vector spaces.

Explores orthogonality, triangle inequality, and the Pythagorean theorem in vector spaces.

Introduces orthogonal and orthonormal families in vector spaces with scalar products.