Mathematical Pictures at a Data Science Exhibition (Hardcover)

This text provides deep and comprehensive coverage of the mathematical background for data science, including machine learning, optimal recovery, compressed sensing, optimization, and neural networks. In the past few decades, heuristic methods adopted by big tech companies have complemented existing scientific disciplines to form the new field of Data Science. This text embarks the readers on an engaging itinerary through the theory supporting the field. Altogether, twenty-seven lecture-length chapters with exercises provide all the details necessary for a solid understanding of key topics in data science. While the book covers standard material on machine learning and optimization, it also includes distinctive presentations of topics such as reproducing kernel Hilbert spaces, spectral clustering, optimal recovery, compressed sensing, group testing, and applications of semidefinite programming. Students and data scientists with less mathematical background will appreciate the appendices that provide more background on some of the more abstract concepts.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Release date:	April 2022
Authors:	Simon Foucart
Dimensions:	235 x 158 x 21mm (L x W x T)
Format:	Hardcover
Pages:	350
ISBN-13:	978-1-316-51888-5
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Applications of computing > Databases > Data capture & analysis Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Promotions
LSN:	1-316-51888-4
Barcode:	9781316518885

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