This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
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This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
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Add this copy of Fundamentals of Data Analytics With a View to Machine to cart. $63.76, new condition, Sold by Books International rated 3.0 out of 5 stars, ships from Toronto, ON, CANADA, published 2021 by Springer Nature Switzerland AG.
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New. Print on demand Contains: Illustrations, black & white, Illustrations, color. XI, 127 p. 41 illus., 28 illus. in color. Intended for professional and scholarly audience.
Add this copy of Fundamentals of Data Analytics: With a View to Machine to cart. $74.82, new condition, Sold by Ria Christie Books rated 4.0 out of 5 stars, ships from Uxbridge, MIDDLESEX, UNITED KINGDOM, published 2021 by Springer Nature Switzerland AG.
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Seller's Description:
New. Contains: Illustrations, black & white, Illustrations, color. XI, 127 p. 41 illus., 28 illus. in color. Intended for professional and scholarly audience.
