ISBN: 9781041124092 - gpt meets game theory: training and optimizing generative ai models (18 risultati)

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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  • Lingua: Inglese

    Editore: Taylor and Francis Ltd, GB, 2026

    1041124090 / 9781041124092

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    Hardback. Condizione: New. Game theory systems can be seen as players working together or competing to achieve goals. GPT Meets Game Theory explores a new way to understand and employ neural networks through the lens of game theory. Focusing on transformers, the engines behind today's most advanced AI, it explains key mathematical concepts and strategies in a clear, accessible way. As AI models are growing larger and taking on more data, GPT Meets Game Theory draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide the models' behavior. It also looks at how these ideas apply to "mean-field" models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved. GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models.…

  • Lingua: Inglese

    Editore: Chapman & Hall, 2026

    1041124090 / 9781041124092

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Hardcover. Condizione: Brand New. 328 pages. 10.00x7.00x10.24 inches. In Stock.

  • Lingua: Inglese

    Editore: Taylor and Francis Ltd, GB, 2026

    1041124090 / 9781041124092

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    Hardback. Condizione: New. Game theory systems can be seen as players working together or competing to achieve goals. GPT Meets Game Theory explores a new way to understand and employ neural networks through the lens of game theory. Focusing on transformers, the engines behind today's most advanced AI, it explains key mathematical concepts and strategies in a clear, accessible way. As AI models are growing larger and taking on more data, GPT Meets Game Theory draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide the models' behavior. It also looks at how these ideas apply to "mean-field" models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved. GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models.…

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, London, 2026

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    Hardcover. Condizione: new. Hardcover. Game theory systems can be seen as players working together or competing to achieve goals. GPT Meets Game Theory explores a new way to understand and employ neural networks through the lens of game theory. Focusing on transformers, the engines behind todays most advanced AI, it explains key mathematical concepts and strategies in a clear, accessible way. As AI models are growing larger and taking on more data, GPT Meets Game Theory draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide the models behavior. It also looks at how these ideas apply to "mean-field" models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved. GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models. This book explores a new way to understand and employ neural networks through the lens of game theory. This is an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, London, 2026

    1041124090 / 9781041124092

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    Hardcover. Condizione: new. Hardcover. Game theory systems can be seen as players working together or competing to achieve goals. GPT Meets Game Theory explores a new way to understand and employ neural networks through the lens of game theory. Focusing on transformers, the engines behind todays most advanced AI, it explains key mathematical concepts and strategies in a clear, accessible way. As AI models are growing larger and taking on more data, GPT Meets Game Theory draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide the models behavior. It also looks at how these ideas apply to "mean-field" models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved. GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models. This book explores a new way to understand and employ neural networks through the lens of game theory. This is an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Lingua: Inglese

    Editore: CRC Press, 2026

    1041124090 / 9781041124092

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    HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

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  • Lingua: Inglese

    Editore: Taylor & Francis Ltd, London, 2026

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    Hardcover. Condizione: new. Hardcover. Game theory systems can be seen as players working together or competing to achieve goals. GPT Meets Game Theory explores a new way to understand and employ neural networks through the lens of game theory. Focusing on transformers, the engines behind todays most advanced AI, it explains key mathematical concepts and strategies in a clear, accessible way. As AI models are growing larger and taking on more data, GPT Meets Game Theory draws from biology, physics, as well as game theory, to help readers understand how we can interpret and guide the models behavior. It also looks at how these ideas apply to "mean-field" models and how they can be used in situations like federated learning, where many devices work together to train an AI system. The book shows how choosing the right AI design and training method is like making strategic moves in a game - especially when multiple AI agents are involved. GPT Meets Game Theory offers an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models, particularly transformers, and also for those who are curious about how game theory can apply to the training and optimisation of these models. This book explores a new way to understand and employ neural networks through the lens of game theory. This is an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models. 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.…

  • Lingua: Inglese

    Editore: Chapman and Hall/CRC, 2026

    1041124090 / 9781041124092

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    Buch. Condizione: Neu. GPT Meets Game Theory | Training and Optimizing Generative AI Models | Hamidou Tembine | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Chapman and Hall/CRC | EAN 9781041124092 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

  • Lingua: Inglese

    Editore: Chapman And Hall/CRC, 2026

    1041124090 / 9781041124092

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    Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book explores a new way to understand and employ neural networks through the lens of game theory. This is an illuminating read for computer science, engineering, and mathematics researchers interested in the mathematical underpinnings of deep learning models.…