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Librería: Basi6 International, Irving, TX, Estados Unidos de America
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Idioma: Inglés
Publicado por Springer-Nature New York Inc, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 2nd edition. 242 pages. 9.25x6.10x9.21 inches. In Stock.
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Añadir al carritoHardcover. Condición: New. 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.
Idioma: Inglés
Publicado por Springer Nature Singapore, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: Buchpark, Trebbin, Alemania
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Añadir al carritoCondición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book. The second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas.
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book.The second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas.
Idioma: Inglés
Publicado por Springer Nature Singapore, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Alemania
EUR 189,90
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Añadir al carritoHardcover. Condición: gut. 2023. Computational Methods for Deep Learning In deutscher Sprache. pages.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Idioma: Inglés
Publicado por Springer, Springer Sep 2023, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 96,29
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book.The second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas. 244 pp. Englisch.
Idioma: Inglés
Publicado por Springer Nature Singapore, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: moluna, Greven, Alemania
EUR 81,44
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Explores advanced topics in deep learning encompassing transformer models, control theory, and graph neural networksPresents detailed mathematical descriptions and algorithms for generative pre-trained models, such as GPTsServes as a valuab.
Idioma: Inglés
Publicado por Springer, Springer Sep 2023, 2023
ISBN 10: 9819948223 ISBN 13: 9789819948222
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 96,29
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book.The second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI).This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 244 pp. Englisch.