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Generated at Fri, 22 Nov 2019 17:26:01 GMT exp-ck: undefined; xpa: undefined;
Electrode, Comp-701350637, DC-prod-dfw7, ENV-prod-a, PROF-PROD, VER-19.1.31, SHA-771c9ce79737366b1d5f53d21cad4086bf722e21, CID-bb496989-c37-16e942630b7fdc, Generated: Fri, 22 Nov 2019 17:26:01 GMT

Geometric and Topological Inference

Walmart # 572331936
$43.00$43.00
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A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science.

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A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science. Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

Specifications

Series Title
Cambridge Texts in Applied Mathematics
Publisher
Cambridge University Press
Book Format
Paperback
Original Languages
English
Number of Pages
246
Author
Jean-Daniel Boissonnat
ISBN-13
9781108410892
Publication Date
March, 2019
Assembled Product Dimensions (L x W x H)
8.96 x 6.42 x 0.63 Inches
ISBN-10
1108410898

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Electrode, Comp-283025139, DC-prod-dfw7, ENV-prod-a, PROF-PROD, VER-30.0.3-ebf-2, SHA-8c8e8dc1c07e462c80c1b82096c2da2858100078, CID-f19b7190-be0-16e942c098f8e8, Generated: Fri, 22 Nov 2019 17:32:24 GMT