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EDIFICIOS DE ESPECTÁCULOS ROMANOS DE LA BÉTICA: ANFITEATROS Y CIRCOS. CARMONA, ITÁLICA Y ÉCIJA
Language: Spanish
Published by UNIVERSIDAD DE SEVILLA, 2025
ISBN 10: 8447224813 ISBN 13: 9788447224814
Rústica. Condition: Nuevo.
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 264 | Sprache: Englisch | Produktart: Bücher | The overwhelming data produced everyday and the increasing performance and cost requirements of applications are 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.
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data, 7)
Book 9 of 95: Studies in Big DataSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data, 7)
Book 9 of 95: Studies in Big DataSeller: Ria Christie Collections, Uxbridge, United Kingdom
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Machine Learning for Adaptive Many-core Machines : A Practical Approach
Book 9 of 95: Studies in Big DataSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Adaptive Many-Core Machines : A Practical Approach
Book 9 of 95: Studies in Big DataSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. pp. 264.
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US$ 176.31
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Add to basketHardcover. Condition: Brand New. 2015 edition. 241 pages. 9.25x6.25x0.75 inches. In Stock.
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Taschenbuch. Condition: Neu. Machine Learning for Adaptive Many-Core Machines - A Practical Approach | Noel Lopes (u. a.) | Taschenbuch | Studies in Big Data | xx | Englisch | 2016 | Springer | EAN 9783319380964 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: New. pp. 261.
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Machine Learning for Adaptive Many-core Machines: A Practical Approach
Language: English
Published by Springer-Verlag New York Inc, 2016
ISBN 10: 3319380966 ISBN 13: 9783319380964
US$ 174.05
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Add to basketPaperback. Condition: Brand New. reprint edition. 264 pages. 9.25x6.10x0.62 inches. In Stock.
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Machine Learning for Adaptive Many-Core Machines : A Practical Approach
Book 9 of 95: Studies in Big DataSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data)
Book 9 of 95: Studies in Big DataUS$ 187.81
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Machine Learning for Adaptive Many-core Machines : A Practical Approach
Book 9 of 95: Studies in Big DataSeller: GreatBookPricesUK, Woodford Green, United Kingdom
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach (Studies in Big Data, 7)
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Edificios de espectáculos romanos de la Bética: anfiteatros y circos
Language: Spanish
Published by Universidad De Sevilla Sep 2025, 2025
ISBN 10: 8447224813 ISBN 13: 9788447224814
Taschenbuch. Condition: Neu. Neuware - Este libro analiza los anfiteatros y circos de la Hispania Ulterior Baetica, especialmente los de Carmo (Carmona), Itálica (Santiponce) y Astigi (Écija), ubicados en la actual provincia de Sevilla. Estas construcciones definían urbanísticamente las ciudades romanas, imitando a Roma con sus funciones para ludi (juegos), incluyendo munera (luchas de gladiadores) y venationes (cacerías). También servían como escenarios políticos y religiosos. La obra actualiza el conocimiento histórico-arqueológico mediante técnicas de prospección geofísica y escáner láser, con especial atención al anfiteatro de Itálica. Los estudios son resultado de proyectos I+D+i de la Universidad de Sevilla, como el ''Proyecto Munera'' y los proyectos sobre Itálica, financiados por instituciones como la Junta de Andalucía y el Ministerio de Ciencia, Innovación y Universidades. Los yacimientos de Carmona e Itálica son gestionados como Conjuntos Arqueológicos.
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Condition: new. Questo è un articolo print on demand.
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Condition: new. Questo è un articolo print on demand.
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach
Book 9 of 95: Studies in Big DataLanguage: English
Published by Springer International Publishing, 2016
ISBN 10: 3319380966 ISBN 13: 9783319380964
US$ 110.38
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in machine learning for adaptive many-core machinesPresents a practical approachWritten by experts in the fieldThe overwhelming data produced everyday and the increasing performance and cost requirements of applic.
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach
Book 9 of 95: Studies in Big DataLanguage: English
Published by Springer International Publishing, 2014
ISBN 10: 3319069373 ISBN 13: 9783319069371
US$ 110.38
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in machine learning for adaptive many-core machinesPresents a practical approachWritten by experts in the fieldThe overwhelming data produced everyday and the increasing performance and cost requirements of applic.
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Add to basketCondition: New. Print on Demand pp. 264 112 Illus. (4 Col.).
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Condition: New. PRINT ON DEMAND pp. 264.
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach
Language: English
Published by Springer, Springer Jul 2014, 2014
ISBN 10: 3319069373 ISBN 13: 9783319069371
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The overwhelming data produced everyday and the increasing performance and cost requirements of applicationsare 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch.
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Machine Learning for Adaptive Many-Core Machines - A Practical Approach
Language: English
Published by Springer, Springer Sep 2016, 2016
ISBN 10: 3319380966 ISBN 13: 9783319380964
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The overwhelming data produced everyday and the increasing performance and cost requirements of applicationsare 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch.
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US$ 197.96
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Add to basketCondition: New. Print on Demand pp. 261.
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Condition: New. PRINT ON DEMAND pp. 261.
