Mathematical pictures at a data science exhibition:
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...
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| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2022
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| Subjects: | |
| Online Access: | DE-12 DE-634 DE-92 DE-91 DE-473 DE-739 Volltext |
| Summary: | 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. |
| Physical Description: | 1 Online-Ressource (xx, 318 Seiten) |
| ISBN: | 9781009003933 |
| DOI: | 10.1017/9781009003933 |
Staff View
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| isbn | 9781009003933 |
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| spelling | Foucart, Simon 1977- Verfasser (DE-588)1041275412 aut Mathematical pictures at a data science exhibition Simon Foucart Cambridge Cambridge University Press 2022 1 Online-Ressource (xx, 318 Seiten) txt rdacontent c rdamedia cr rdacarrier 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. Big data / Mathematics Information science / Mathematics Computer science / Mathematics Data Science (DE-588)1140936166 gnd rswk-swf Angewandte Mathematik (DE-588)4142443-8 gnd rswk-swf Angewandte Mathematik (DE-588)4142443-8 s Data Science (DE-588)1140936166 s DE-604 Erscheint auch als Druck-Ausgabe 978-1-31-651888-5 https://doi.org/10.1017/9781009003933 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Foucart, Simon 1977- Mathematical pictures at a data science exhibition Big data / Mathematics Information science / Mathematics Computer science / Mathematics Data Science (DE-588)1140936166 gnd Angewandte Mathematik (DE-588)4142443-8 gnd |
| subject_GND | (DE-588)1140936166 (DE-588)4142443-8 |
| title | Mathematical pictures at a data science exhibition |
| title_auth | Mathematical pictures at a data science exhibition |
| title_exact_search | Mathematical pictures at a data science exhibition |
| title_exact_search_txtP | Mathematical pictures at a data science exhibition |
| title_full | Mathematical pictures at a data science exhibition Simon Foucart |
| title_fullStr | Mathematical pictures at a data science exhibition Simon Foucart |
| title_full_unstemmed | Mathematical pictures at a data science exhibition Simon Foucart |
| title_short | Mathematical pictures at a data science exhibition |
| title_sort | mathematical pictures at a data science exhibition |
| topic | Big data / Mathematics Information science / Mathematics Computer science / Mathematics Data Science (DE-588)1140936166 gnd Angewandte Mathematik (DE-588)4142443-8 gnd |
| topic_facet | Big data / Mathematics Information science / Mathematics Computer science / Mathematics Data Science Angewandte Mathematik |
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