Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, Cambridge, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Paperback. Condizione: new. Paperback. 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. This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in particular. It will also be valuable to data scientists seeking mathematical sophistication. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
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Editore: Cambridge University Press 2022-05, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
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Editore: Cambridge University Press, Cambridge, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. 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. This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in particular. It will also be valuable to data scientists seeking mathematical sophistication. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: Toscana Books, AUSTIN, TX, U.S.A.
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
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Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. New edition NO-PA16APR2015-KAP.
Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 136,03
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
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Aggiungi al carrelloPaperback. Condizione: Brand New. 350 pages. 9.00x6.00x0.71 inches. In Stock. This item is printed on demand.
Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 49,48
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Editore: Cambridge University Press, Cambridge, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
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EUR 56,25
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. 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. This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in particular. It will also be valuable to data scientists seeking mathematical sophistication. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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EUR 57,73
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in par.
Editore: Cambridge University Press, Cambridge, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 79,09
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. 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. This text explores a diverse set of data science topics through a mathematical lens, helping mathematicians become acquainted with data science in general, and machine learning, optimal recovery, compressive sensing, optimization, and neural networks in particular. It will also be valuable to data scientists seeking mathematical sophistication. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 100,96
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Aggiungi al carrelloHardcover. Condizione: Brand New. 350 pages. 9.00x6.00x0.81 inches. In Stock. This item is printed on demand.
Editore: Cambridge University Press, 2022
ISBN 10: 1316518884 ISBN 13: 9781316518885
Lingua: Inglese
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 104,00
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Aggiungi al carrelloHardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 650.
Editore: Cambridge University Press, 2022
ISBN 10: 100900185X ISBN 13: 9781009001854
Lingua: Inglese
Da: preigu, Osnabrück, Germania
EUR 60,10
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Mathematical Pictures at a Data Science Exhibition | Simon Foucart | Taschenbuch | Kartoniert / Broschiert | Englisch | 2022 | Cambridge University Press | EAN 9781009001854 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.