ISBN: 9780262048644 - understanding deep learning (39 resultados)

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  • Idioma: Inglés

    Editorial: The MIT Press (edition ), 2023

    0262048647 / 9780262048644

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    Hardcover. Condición: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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    Hardback. Condición: Very Good. 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 Notebooks.…

  • Idioma: Inglés

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    Hardback. Condición: Very Good. 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 Notebooks.…

  • Idioma: Inglés

    Editorial: MIT Press, 2023

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    Condición: Fine. Used book that is in almost brand-new condition. May contain a remainder mark. Better World Books: Buy Books. Do Good.

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Editorial: Penguin Random House, 2023

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  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: 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.

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

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    Editorial: The MIT Press, 2023

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  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: 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.

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Editorial: MIT Press Ltd, 2023

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    Hardcover. Condición: new. Hardcover. An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice.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 modelsShort, focused chapters progress in complexity, easing students into difficult conceptsPragmatic approach straddling theory and practice gives readers the level of detail required to implement naive versions of modelsStreamlined presentation separates critical ideas from background context and extraneous detailMinimal mathematical prerequisites, extensive illustrations, and practice problems make challenging material widely accessibleProgramming exercises offered in accompanying Python Notebooks "This book covers modern deep learning and tackles supervised learning, model architecture, unsupervised learning, and deep reinforcement learning"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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  • Idioma: Inglés

    Editorial: MIT Press, 2023

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    hardcover. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

  • Idioma: Inglés

    Editorial: MIT Press Ltd, US, 2023

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  • Idioma: Inglés

    Editorial: The MIT Press Dez 2023, 2023

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    Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, AlemaniaRheinberg-Buch Andreas Meier eK

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    Buch. Condición: 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.…

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    Editorial: The MIT Press Dez 2023, 2023

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Buch. Condición: 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.…

  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: As New. Unread book in perfect condition.

  • Idioma: Inglés

    Editorial: The MIT Press Dez 2023, 2023

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    Buch. Condición: 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.…

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    Editorial: The MIT Press, 2023

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    Librería: Speedyhen, Hertfordshire, Reino UnidoSpeedyhen

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  • Idioma: Inglés

    Editorial: The MIT Press, 2023

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    Condición: New. In English.

  • Idioma: Inglés

    Editorial: MIT Press, 2023

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    Condición: 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 .

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    Editorial: MIT Academic, 2023

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    Condición: New. 2023. Hardcover. . . . . .

  • Idioma: Inglés

    Editorial: The MIT Press Dez 2023, 2023

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    Buch. Condición: 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 BuchEasy Access System Europe Oü, 16879218, Mustamäe tee 50, 10621, Tallinn, Estonia, Tallinn Englisch.…

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    Editorial: MIT PRESS, 2023

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    Hardcover. Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

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    Editorial: The MIT Press, 2023

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    Buch. Condición: 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.