Isbn: 9780262048644 - understanding deep learning (35 risultati)

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Hardcover. Condizione: 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.…

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Buch. Condizione: 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.…

Buch. Condizione: 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.…

Buch. Condizione: 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.…

Condizione: 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 .

Condizione: New. 2023. Hardcover. . . . . .

Buch. Condizione: 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, EU GPSR Authorised Representative, Englisch.…

Buch. Condizione: Neu. Understanding Deep Learning | Simon J. D. Prince | Buch | 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.

Hardback. Condizione: New.

Hardcover. Condizione: New Books. 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.…

Hardcover. Condizione: Brand New. 496 pages. 9.25x8.25x1.50 inches. In Stock.