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Mathematics of Data

By: Mahoney, Michael W [edt].
Contributor(s): Duchi, John C [edt] | Gilbert, Anna C [edt].
Material type: materialTypeLabelBookSeries: IAS/​Park City mathematics series ; v. 25.Publisher: USA : American Mathematical Society, 2018Description: xii, 325 p. : ill. ; 26 cm.ISBN: 9781470435752.Subject(s): Big data | Mathematics | Mathematics teachers | Linear and multilinear algebra | Matrix theory | Research exposition | Convex and discrete geometry | Probability theory | Stochastic processes | Statistics | Numerical analysis | Computer science | Operations research | Mathematical programmingDDC classification: 510 Summary: Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.
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Books 510 MAH (Browse shelf) Available 032000

Includes bibliographical references.

Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.

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