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Synopsis
Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.
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Implementation of Machine Learning Algorithms Using Control-flow and Dataflow Paradigms
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Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Published by
Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Print on DemandSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Implementation of Machine Learning Algorithms Using Control-flow and Dataflow Paradigms
Published by
Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
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Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Implementation of Machine Learning Algorithms Using Control-flow and Dataflow Paradigms
Published by
Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
New
Softcover
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 44200079-n
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Implementation of Machine Learning Algorithms Using Control-flow and Dataflow Paradigms
Published by
Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
Used
Softcover
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition. Seller Inventory # 44200079
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. The presents research of energy efficient accelerators for machine learning . Seller Inventory # 847489864
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Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms
Published by
Engineering Science Reference, 2022
ISBN 10: 1799883515
ISBN 13: 9781799883517
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians. Seller Inventory # 9781799883517
Quantity: 1 available