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Explores kernel regression, the curse of dimensionality, and random features in neural networks.
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Explores orthogonality between vectors and subspaces, demonstrating practical implications in matrix operations.
Dimension Calculation in Linear Algebra
Covers the calculation of dimensions in linear algebra, focusing on determining the dimension of the kernel of a given matrix.
Singular homology
Introduces singular homology, defining singular simplices and explaining the chain complex construction.
Isomorphism Theorems: Quotients of Group
Explores the isomorphism theorems for quotient groups and the concept of surjective homomorphisms.
Linear Applications in Vector Spaces
Discusses linear applications between vector spaces and properties of endomorphisms and automorphisms.
Linear Maps and Bases: The Rank Theorem
Covers bijective linear maps, invertibility of matrices, isomorphisms, and the rank theorem.
Linear Applications: Vector Spaces and Subspaces
Explores linear applications in vector spaces, emphasizing subspaces and properties of linear maps.
Linear Algebra: Systems and Subspaces
Covers linear systems, vector subspaces, and the kernel and image of linear applications.

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