Matrices and vectors. Linear systems. Gaussian elimination and LU factorization. Orthogonality: projections, orthogonalization and least squares. Decomposition into singular values. Eigenvalues and eigenvectors. Introduction to numerical analysis: stability and conditioning. Applications: reduction of dimensionality and main components; PageRank algorithm and equivalents.
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