Artículos relacionados a The Geometry of Intelligence: Foundations of Transformer...
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning: 175 (Studies in Big Data) - Tapa dura
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Dr. Pradeep Singh earned his Ph.D. and Master’s degrees from the Indian Institute of Technology (IIT) Delhi, specializing in Symbolic Systems, and a Bachelor's degree in Data Science from IIT Madras. Currently, he is a Post-Doctoral Researcher and Principal Investigator at the Machine Intelligence Lab within the Department of Computer Science and Engineering at IIT Roorkee, where he is actively engaged in research at the intersection of Geometric Deep Learning, Neuro-symbolic AI, and Dynamical Systems. His research is supported by the National Post Doctoral Fellowship (N-PDF) from the Science and Engineering Research Board (SERB), Department of Science and Technology. Dr. Singh has earned multiple accolades, including All India Rank 1 in IIT GATE 2020, IIT JAM 2015, and CSIR NET 2019, along with prestigious fellowships such as the National Board for Higher Mathematics (NBHM) Masters, Doctoral, and Post Doctoral Fellowships from the Department of Atomic Energy, India. In 2019, he was one of only two researchers nationwide to be awarded the esteemed Shyama Prasad Mukherjee (SPM) Doctoral Fellowship in Mathematics by the Council of Scientific and Industrial Research, India.
Dr. Balasubramanian Raman received his Ph.D. from IIT Madras and his B.Sc. and M.Sc. in Mathematics from the University of Madras. He is a Professor and the Head of the Department of Computer Science and Engineering at IIT Roorkee, as well as the iHUB Divyasampark Chair Professor. He is also a Joint Faculty member in the Mehta Family School of Data Science and Artificial Intelligence at IIT Roorkee. With over 200 research papers published in reputed journals and conferences, his research interests span Machine Learning, Image and Video Processing, Computer Vision, and Pattern Recognition. Dr. Raman has served as a Guest Professor and Visiting Researcher at prestigious institutions such as Osaka Metropolitan University, Curtin University, the University of Cyberjaya, and the University of Windsor. He has held postdoctoral positions at Rutgers University and the University of Missouri-Columbia. Under his coaching, teams have achieved notable rankings in the ACM International Collegiate Programming Contest (ICPC) World Finals. He has been recognized with several awards, including the BOYSCAST Fellowship and the Ramkumar Prize for Outstanding Teaching and Research.
De la contraportada
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
- EditorialSpringer-Verlag GmbH
- Año de publicación2025
- ISBN 10 9819647053
- ISBN 13 9789819647057
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de páginas384
- Contacto del fabricanteno disponible
EUR 130,04
EUR 17,55 gastos de envío desde Estados Unidos de America a España
Destinos, gastos y plazos de envíoComprar nuevo
Ver este artículo
EUR 106,99
EUR 11,00 gastos de envío desde Alemania a España
Destinos, gastos y plazos de envíoResultados de la búsqueda para The Geometry of Intelligence: Foundations of Transformer...
Imagen del vendedor
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
Publicado por
Springer Nature Singapore Jun 2025, 2025
ISBN 10: 9819647053
ISBN 13: 9789819647057
Nuevo
Tapa dura
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: 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. Nº de ref. del artículo: 9789819647057
Cantidad disponible: 2 disponibles
Imagen del vendedor
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
Publicado por
Springer Nature Singapore, Springer Nature Singapore, 2025
ISBN 10: 9819647053
ISBN 13: 9789819647057
Nuevo
Tapa dura
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9789819647057
Cantidad disponible: 1 disponibles
Imagen de archivo
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning (Studies in Big Data, 175)
Librería: California Books, Miami, FL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: I-9789819647057
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Geometry of Intelligence : Foundations of Transformer Networks in Deep Learning
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 50259100-n
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 2202231800
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning
Publicado por
Springer Nature Singapore, Springer Nature Singapore Mai 2025, 2025
ISBN 10: 9819647053
ISBN 13: 9789819647057
Nuevo
Tapa dura
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 384 pp. Englisch. Nº de ref. del artículo: 9789819647057
Cantidad disponible: 1 disponibles
Imagen de archivo
Geometry of Intelligence : Foundations of Transformer Networks in Deep Learning
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Nº de ref. del artículo: 50259100-n
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Geometry of Intelligence : Foundations of Transformer Networks in Deep Learning
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 50259100
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
Geometry of Intelligence : Foundations of Transformer Networks in Deep Learning
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 50259100
Cantidad disponible: Más de 20 disponibles
Imagen de archivo
The Geometry of Intelligence: Foundations of Transformer Networks in Deep Learning (Hardcover)
Publicado por
Springer Nature Switzerland AG, Cham, 2025
ISBN 10: 9819647053
ISBN 13: 9789819647057
Nuevo
Tapa dura
Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: 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 UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9789819647057
Cantidad disponible: 1 disponibles