Mathematics of Data Science

A Computational Approach to Clustering and Classification

von

Calvetti, DanielaSomersalo, Erkki

BuchPaperback

Verkaufsrang24234inMathematik

CHF81.90

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Provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms.

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Details

ISBN/GTIN978-1-61197-636-6

ProduktartBuch

EinbandPaperback

VerlagSociety for Industrial & Applied Mathematics,U.S.

Erscheinungsdatum28.02.2021

ReiheData Science

Seiten189 Seiten

SpracheEnglisch

Gewicht422 g

WarengruppeNaturwissenschaft

KategorieMathematik

Weitere Details

Reihe

Data Science

Mathematics of Data Science

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Data Science

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Über die Autorin/den Autor

Calvetti, DanielaSomersalo, Erkki

Daniela Calvetti is the James Wood Williamson Professor in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University. Her research interests, strongly rooted in numerical analysis, include inverse problems, uncertainty quantification, and mathematical modeling, with a specific focus on human metabolism and the brain. She is a member of SIAM and the International Society for Cerebral Blood Flow and Metabolism.Erkki Somersalo is a professor in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University, with a background in analysis and partial differential equations. His research interests include computational inverse problems, with an emphasis on Bayesian methods, and applications to a wide range of areas, particularly to medical imaging. He is a founding member of the Finnish Inverse Problems Society and a member of the Finnish Academy of Sciences and Letters and SIAM. He is also a fellow of the Institute of Physics, UK.