Geometry Intelligence Foundations Transformer by Singh Pradeep (15 results)

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  • Language: English

    Published by Springer, 2025

    9819647053 / 9789819647057

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  • Language: English

    Published by Springer Nature Switzerland AG, Cham, 2025

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    Hardcover. Condition: new. Hardcover. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Language: English

    Published by Springer, 2025

    9819647053 / 9789819647057

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  • Language: English

    Published by Springer, 2025

    9819647053 / 9789819647057

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  • Language: English

    Published by Springer, 2025

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  • Language: English

    Published by Palgrave Macmillan, 2026

    9819647088 / 9789819647088

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    Taschenbuch. Condition: Neu. The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning | Pradeep Singh (u. a.) | Taschenbuch | Studies in Big Data | xxi | Englisch | 2026 | Palgrave Macmillan | EAN 9789819647088 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Language: English

    Published by Springer, 2025

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  • Language: English

    Published by Springer Nature Switzerland AG, CH, 2025

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    Hardback. Condition: New. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers.

  • Language: English

    Published by Springer-Nature New York Inc, 2025

    9819647053 / 9789819647057

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    Hardcover. Condition: Brand New. 382 pages. 9.25x6.10x9.21 inches. In Stock.

  • Language: English

    Published by Springer Nature Switzerland AG, Cham, 2025

    9819647053 / 9789819647057

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    Hardcover. Condition: new. Hardcover. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Language: English

    Published by Springer Nature Switzerland AG, CH, 2025

    9819647053 / 9789819647057

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    Hardback. Condition: New. This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers.

  • Language: English

    Published by Springer, 2025

    9819647053 / 9789819647057

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  • Language: English

    Published by Springer Nature Singapore Jun 2025, 2025

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    Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers. 361 pp. Englisch.

  • Language: English

    Published by Springer Verlag GmbH, 2025

    9819647053 / 9789819647057

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

  • Language: English

    Published by Springer, Springer Mai 2025, 2025

    9819647053 / 9789819647057

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    Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers an in-depth exploration of the mathematical foundations underlying transformer networks, the cornerstone of modern AI across various domains. Unlike existing literature that focuses primarily on implementation, this work delves into the elegant geometry, symmetry, and mathematical structures that drive the success of transformers. Through rigorous analysis and theoretical insights, the book unravels the complex relationships and dependencies that these models capture, providing a comprehensive understanding of their capabilities. Designed for researchers, academics, and advanced practitioners, this text bridges the gap between practical application and theoretical exploration. Readers will gain a profound understanding of how transformers operate in abstract spaces, equipping them with the knowledge to innovate, optimize, and push the boundaries of AI. Whether you seek to deepen your expertise or pioneer the next generation of AI models, this book is an essential resource on the mathematical principles of transformers.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 384 pp. Englisch.