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Añadir al carritoCondición: good. The item shows wear from consistent use, but it remains in good condition and works perfectly. All pages and cover are intact including the dust cover, if applicable . Spine may show signs of wear. Pages may include limited notes and highlighting. May NOT include discs, access code or other supplemental materials.
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Añadir al carritoCondición: very_good. Book has little sign of wear or use.
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Añadir al carritoCondición: acceptable. Used - Acceptable: All pages and the cover are intact, but shrink wrap, dust covers, or boxed set case may be missing. Pages may include limited notes, highlighting, or minor water damage but the text is readable. Item may be missing bundled media.
Publicado por Springer
Librería: Academic Book Solutions, Medford, NY, Estados Unidos de America
EUR 10,63
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Añadir al carritohardcover. Condición: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 34,71
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Añadir al carritopaperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 35,72
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Añadir al carritopaperback. Condición: Very Good.
EUR 27,72
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Añadir al carritoSoft cover. Condición: Fine.
Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030931579 ISBN 13: 9783030931575
Idioma: Inglés
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 40,83
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Añadir al carritoHRD. Condición: Used - Good. Used Book. Shipped from UK. Established seller since 2000.
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Añadir al carritoCondición: New.
EUR 46,53
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Añadir al carritoCondición: New.
Publicado por Springer Nature Switzerland AG, 2023
ISBN 10: 3030931609 ISBN 13: 9783030931605
Idioma: Inglés
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 52,47
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
EUR 46,08
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EUR 48,89
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 57,38
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Añadir al carritoCondición: New.
Librería: Academic US, Piscataway, NJ, Estados Unidos de America
EUR 56,21
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Añadir al carritoCondición: New. This book is in good condition.
EUR 48,14
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Añadir al carritoCondición: New.
Publicado por Springer Nature Switzerland AG, CH, 2023
ISBN 10: 3030931609 ISBN 13: 9783030931605
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 64,64
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Añadir al carritoPaperback. Condición: New. 2022 ed. This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions.Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github.The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.
EUR 47,61
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Añadir al carritoPaperback. Condición: New.
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Añadir al carritoCondición: New.
EUR 52,77
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Añadir al carritoCondición: New. In.
Publicado por Springer
Librería: Academic Book Solutions, Medford, NY, Estados Unidos de America
EUR 41,84
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Añadir al carritohardcover. Condición: VeryGood. A copy that may have been read, very minimal wear and tear. May have a remainder mark.
EUR 54,21
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Añadir al carritoCondición: As New. Unread book in perfect condition.
ISBN 10: 3031640861 ISBN 13: 9783031640865
Idioma: Inglés
Librería: Books From California, Simi Valley, CA, Estados Unidos de America
EUR 49,14
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Añadir al carritohardcover. Condición: Very Good.
Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030931579 ISBN 13: 9783030931575
Idioma: Inglés
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 77,00
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Publicado por Springer Nature Switzerland AG, 2022
ISBN 10: 3030931579 ISBN 13: 9783030931575
Idioma: Inglés
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 72,18
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Publicado por Springer-Nature New York Inc, 2023
ISBN 10: 3030931609 ISBN 13: 9783030931605
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
EUR 58,65
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Añadir al carritoPaperback. Condición: Brand New. 215 pages. 9.25x6.10x0.46 inches. In Stock.
Publicado por Springer Nature Switzerland AG, CH, 2022
ISBN 10: 3030931579 ISBN 13: 9783030931575
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 88,84
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Añadir al carritoHardback. Condición: New. 2022 ed. This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions.Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github.The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.
Publicado por Springer International Publishing, Springer International Publishing Sep 2024, 2024
ISBN 10: 3031640861 ISBN 13: 9783031640865
Idioma: Inglés
Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, Alemania
EUR 64,19
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Añadir al carritoBuch. Condición: Neu. Neuware 340 pp. Englisch.