dimensionality-reduction
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Mathematics of Data Science
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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.