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Lecture
Gram-Schmidt Process
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Related lectures (27)
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Orthogonal Bases and Projection
Introduces orthogonal bases, projection onto subspaces, and the Gram-Schmidt process in linear algebra.
Orthogonal Vectors and Projections
Covers scalar products, orthogonal vectors, norms, and projections in vector spaces, emphasizing orthonormal families of vectors.
Projection in Vector Spaces
Explores the generalization of projection in vector spaces and its unique properties, emphasizing its role in finding the closest vector in a subspace.
Orthogonal Bases in Vector Spaces
Covers the concept of orthogonal bases in vector spaces and Pythagorean theorem applications.
Orthogonalization of Vectors
Covers the Gram-Schmidt orthogonalization process and vector projections in a vector space.
Orthogonal Complement and Projection
Covers the concept of orthogonal complement and projection in vector spaces.
Orthogonality and Projection
Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.
Orthogonal Projection Theorems
Covers the theorems related to orthogonal projection and orthonormal bases.
Orthogonal Families and Projections
Explains orthogonal families, bases, and projections in vector spaces.
Singular Value Decomposition: Applications and Interpretation
Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.
