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Computational Methods for Deep Learning: Theory, Algorithms, and Implementations (Texts in Computer Science) - Hardcover
- PublisherSpringer
- Publication date2023
- ISBN 10 9819948223
- ISBN 13 9789819948222
- BindingHardcover
- LanguageEnglish
- Edition number2
- Number of pages242
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Computational Methods for Deep Learning
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Computational Methods for Deep Learning
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Computational Methods for Deep Learning
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COMPUTATIONAL METHODS FOR DEEP LEARNING THEORY ALGORITHMS AND IMPLEMENTATIONS 2ED (HB 2023)
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Computational Methods for Deep Learning
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Computational Methods for Deep Learning
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Computational Methods for Deep Learning
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Computational Methods for Deep Learning: Theory, Algorithms, and Implementations (Texts in Computer Science)
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Computational Methods for Deep Learning
Published by
Springer Nature Singapore, 2023
ISBN 10: 9819948223
ISBN 13: 9789819948222
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Condition: 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. Seller Inventory # 892114947
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Computational Methods for Deep Learning
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Springer Nature Singapore Okt 2023, 2023
ISBN 10: 9819948223
ISBN 13: 9789819948222
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Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: 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. Seller Inventory # 9789819948222
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