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Mathematical Pictures at a Data Science Exhibition

Mathematical Pictures at a Data Science Exhibition

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Mathematical Pictures at a Data Science Exhibition

Mathematical Pictures at a Data Science Exhibition

Category

Data Science

Math

Author

Simon Foucart

Publication

Cambridge University Press

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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.

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ISBN-10

1316518884

ISBN-13

978-1316518885

Publisher

Cambridge University Press

Price

99.99

File Type

PDF

Page No.

350

Simon Foucart

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Review

What a great read and a unique perspective! It contains a beautifully written rigorous treatment of many areas of Mathematical Data Science - perfect for a graduate course or for scholars of related backgrounds. The presentation and walk through of the topic are a great way to motivate its study. Deanna Needell, University of California, Los Angeles

The title perfectly captures the books approach, and the author is a wonderful guide to this gallery. He sticks to the facts and gives a cogent yet thorough description of the most foundational mathematical results. The book will fill in some missing mathematical background for many of us working in data science, and the exercises make it an excellent class text as well. Stephen Wright, University of Wisconsin - Madison

With Mathematical Pictures at a Data Science Exhibition, Simon Foucart has deftly illuminated the mathematical side of data science with a rigorous yet accessible treatment. This book, like a good museum, will be a valuable resource for experts, students, and casual enthusiasts. Richard Baraniuk, Rice University

Book Description

A diverse selection of data science topics explored through a mathematical lens.

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