Canonical Correlation Analysis: Exercises Solutions

Related lectures (27)

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Explores polynomial operations, properties, and subspaces in vector spaces.

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

Explores Kernel Principal Component Analysis, a nonlinear method using kernels for linear problem solving and dimensionality reduction.

Explains orthogonal families, bases, and projections in vector spaces.

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 the theorems related to orthogonal projection and orthonormal bases.

Introduces orthogonal families, orthonormal bases, and projections in linear algebra.

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

Explains the construction of U, verification of results, and interpretation of SVD in matrix decomposition.