data-science
Latest stories covering data-science, with summaries and links to related coverage.
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Mathematics of Data Science
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1 min read
The book "Mathematics of Data Science" covers the mathematical foundations essential for data science applications. Key topics include high-dimensional analysis, singular value decomposition, principal component analysis, linear regression, clustering, and dimension reduction techniques.
The early History of the Singular Value Decomposition (1993) [pdf]
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1 min read
The Singular Value Decomposition (SVD) is a mathematical technique used in linear algebra for decomposing a matrix into singular values and vectors. It has applications in various fields, including statistics, signal processing, and machine learning.