9789811634192 - distributed machine learning and gradient optimization di jiang, jiawei; cui, bin; zhang, ce (15 risultati)
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Hardcover. Condizione: new. Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Lingua: Inglese
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Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Lingua: Inglese
Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Condizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer, Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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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, imp…lementing 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.
Distributed Machine Learning and Gradient Optimization
Jiang, Jiawei (Author)/ Cui, Bin (Author)/ Zhang, Ce (Author)
Lingua: Inglese
Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 180 pages. 9.25x6.10x0.50 inches. In Stock.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Hardcover. Condizione: new. Hardcover. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Singapore|Springer 2021
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: moluna, Greven, , Germaniamoluna
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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.
Lingua: Inglese
Editore: Springer Nature Singapore Feb 2022 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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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 syste…ms. 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.
Lingua: Inglese
Editore: Springer, Springer Feb 2022 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 184 pp. Englisch.
Lingua: Inglese
Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer 2022
Serie: Big Data Management, Libro 5 di 4. Libro 5 di 4 - Big Data Management
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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