Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: Better World Books Ltd, Dunfermline, Vereinigtes Königreich
EUR 29,54
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 32,40
Anzahl: 1 verfügbar
In den WarenkorbZustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1500grams, ISBN:9781107011793.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
EUR 81,44
Anzahl: 1 verfügbar
In den WarenkorbZustand: New.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
EUR 91,19
Anzahl: 11 verfügbar
In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 99,88
Anzahl: 1 verfügbar
In den WarenkorbZustand: New. pp. 598 357 Illus. (Col.).
EUR 99,57
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Anbieter: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Deutschland
Gebunden. Zustand: Sehr gut. Gebraucht - Sehr gut Leichte Lagerspuren -An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today's increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics. 544 pp. Englisch.
EUR 104,14
Anzahl: 16 verfügbar
In den WarenkorbZustand: New. In.
EUR 79,91
Anzahl: 16 verfügbar
In den WarenkorbZustand: NEW.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New. 2012. 1st Edition. Hardcover. A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms. Num Pages: 598 pages, 357 colour illus. 5 tables 201 exercises. BIC Classification: UYQV. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 255 x 187 x 32. Weight in Grams: 1428. Models, Learning, and Inference. 598 pages, 357 colour illus. 5 tables 201 exercises. A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms. Cateogry: (P) Professional & Vocational; (U) Tertiary Education (US: College). BIC Classification: UYQV. Dimension: 255 x 187 x 32. Weight: 1422. . . . . . Books ship from the US and Ireland.
EUR 88,79
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. Simon J. D. Prince is Honorary Professor of Computer Science at the University of Bath and author of Computer Vision: Models, Learning and Inference. A research scientist specializing in artificial intelligence and deep learning, he has led teams of .
Buch. Zustand: Neu. Neuware -An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today's increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.- Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models- Short, focused chapters progress in complexity, easing students into difficult concepts - Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models- Streamlined presentation separates critical ideas from background context and extraneous detail- Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible - Programming exercises offered in accompanying Python Not Elektronisches BuchLibri GmbH, Europaallee 1, 36244 Bad Hersfeld Englisch.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: moluna, Greven, Deutschland
Zustand: New. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate stude.
EUR 144,62
Anzahl: 1 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 496 pages. 9.25x8.25x1.50 inches. In Stock.
Buch. Zustand: Neu. Understanding Deep Learning | Simon J. D. Prince | Buch | Einband - fest (Hardcover) | Englisch | 2023 | The MIT Press | EAN 9780262048644 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Sprache: Englisch
Verlag: Cambridge University Press, 2012
ISBN 10: 1107011795 ISBN 13: 9781107011793
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering.
EUR 173,29
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. 2023. Hardcover. . . . . . Books ship from the US and Ireland.
Buch. Zustand: Neu. Neuware - An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today's increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.- Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models- Short, focused chapters progress in complexity, easing students into difficult concepts - Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models- Streamlined presentation separates critical ideas from background context and extraneous detail- Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible - Programming exercises offered in accompanying Python Not Elektronisches Buch.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 165,43
Anzahl: 2 verfügbar
In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 632 pages. 10.10x7.00x1.30 inches. In Stock.
Buch. Zustand: Neu. Neuware -An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.Deep learning is a fast-moving field with sweeping relevance in today's increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject, covering all the key topics along with recent advances and cutting-edge concepts. Many deep learning texts are crowded with technical details that obscure fundamentals, but Simon Prince ruthlessly curates only the most important ideas to provide a high density of critical information in an intuitive and digestible form. From machine learning basics to advanced models, each concept is presented in lay terms and then detailed precisely in mathematical form and illustrated visually. The result is a lucid, self-contained textbook suitable for anyone with a basic background in applied mathematics.- Up-to-date treatment of deep learning covers cutting-edge topics not found in existing texts, such as transformers and diffusion models- Short, focused chapters progress in complexity, easing students into difficult concepts - Pragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of models- Streamlined presentation separates critical ideas from background context and extraneous detail- Minimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessible - Programming exercises offered in accompanying Python Not Elektronisches Buch Englisch.
Anbieter: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Deutschland
Hardcover. Zustand: gut. 2012. Computer Vision. Models, Learning and Inference In deutscher Sprache. pages.