Articoli correlati a Distributed Machine Learning and Gradient Optimization
- EditoreSpringer-Nature New York Inc
- Data di pubblicazione2022
- ISBN 10 981163419X
- ISBN 13 9789811634192
- RilegaturaCopertina rigida
- LinguaInglese
- Numero edizione1
- Numero di pagine184
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Distributed Machine Learning and Gradient Optimization
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Distributed Machine Learning and Gradient Optimization (Big Data Management)
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Distributed Machine Learning and Gradient Optimization (Big Data Management)
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Distributed Machine Learning and Gradient Optimization (Big Data Management)
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Distributed Machine Learning and Gradient Optimization
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Springer Nature Singapore Feb 2022, 2022
ISBN 10: 981163419X
ISBN 13: 9789811634192
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution. Focusing on methods that can speed up large-scale gradient optimization through both algorithm optimizations and careful system implementations, the book introduces three essential techniques in designing a gradient optimization algorithm to train a distributed machine learning model: parallel strategy, data compression and synchronization protocol.Written in a tutorial style, it covers a range of topics, from fundamental knowledge to a number of carefully designed algorithms and systems of distributed machine learning. It will appealto a broad audience in the field of machine learning, artificial intelligence, big data and database management. 184 pp. Englisch. Codice articolo 9789811634192
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Distributed Machine Learning and Gradient Optimization
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Springer, Berlin|Springer Nature Singapore|Springer, 2021
ISBN 10: 981163419X
ISBN 13: 9789811634192
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, imp. Codice articolo 473138653
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Distributed Machine Learning and Gradient Optimization
Editore:
Springer Nature Singapore, Springer Nature Singapore, 2022
ISBN 10: 981163419X
ISBN 13: 9789811634192
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution. Focusing on methods that can speed up large-scale gradient optimization through both algorithm optimizations and careful system implementations, the book introduces three essential techniques in designing a gradient optimization algorithm to train a distributed machine learning model: parallel strategy, data compression and synchronization protocol.Written in a tutorial style, it covers a range of topics, from fundamental knowledge to a number of carefully designed algorithms and systems of distributed machine learning. It will appealto a broad audience in the field of machine learning, artificial intelligence, big data and database management. Codice articolo 9789811634192
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Distributed Machine Learning and Gradient Optimization (Big Data Management)
Da: California Books, Miami, FL, U.S.A.
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