Tag: numerical-linear-algebra

The applications of Singular Value Decomposition (SVD) are manifold. In this post, we will focus on the application of SVD to PCA, which is a great tool for dimensionality reduction.

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A QR factorization is a factorization of a matrix A into a product A = QR of an orthogonal matrix Q and an upper triangular matrix R. This kind of decomposition is useful in solving linear least squares problems and in the eigendecomposition of a matrix, which shows the structure of the matrix in terms of its eigenvalues and eigenvectors.

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Linear systems of equations are the bread and butter of numerical linear algebra. Solving them is at the core of many machine learning algorithms and engineering applications.

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Floating-Point arithmetic is a way of representing real numbers in a computer. It is a way of representing numbers in a computer that is not exact, but is fast and efficient. It is a fundamental concept in numerical computing.

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