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Machine Learning for Adaptive Many-Core Machines - A Practical Approach / / by Noel Lopes, Bernardete Ribeiro



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Autore: Lopes Noel Visualizza persona
Titolo: Machine Learning for Adaptive Many-Core Machines - A Practical Approach / / by Noel Lopes, Bernardete Ribeiro Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (251 p.)
Disciplina: 006.31
Soggetto topico: Computational intelligence
Artificial intelligence
Operations research
Decision making
Computational Intelligence
Artificial Intelligence
Operations Research/Decision Theory
Persona (resp. second.): RibeiroBernardete
Note generali: Includes index.
Nota di contenuto: Introduction -- Supervised Learning -- Unsupervised and Semi-supervised Learning -- Large-Scale Machine Learning.
Sommario/riassunto: The overwhelming data produced everyday and the increasing performance and cost requirements of applications is transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together.
Titolo autorizzato: Machine Learning for Adaptive Many-Core Machines - A Practical Approach  Visualizza cluster
ISBN: 3-319-06938-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910739476403321
Lo trovi qui: Univ. Federico II
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Serie: Studies in Big Data, . 2197-6503 ; ; 7