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000723351 019__ $$a894169887
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000723351 0247_ $$a10.1007/978-3-319-06938-8$$2doi
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000723351 035__ $$aSP(OCoLC)882914135$$z(OCoLC)894169887
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000723351 049__ $$aISEA
000723351 050_4 $$aQ325.5
000723351 08204 $$a006.3/1$$223
000723351 1001_ $$aLopes, Noel,$$eauthor.
000723351 24510 $$aMachine learning for adaptive many-core machines -- a practical approach$$h[electronic resource] /$$cNoel Lopes, Bernardete Ribeiro.
000723351 264_1 $$aCham :$$bSpringer,$$c2015.
000723351 300__ $$a1 online resource (xx, 241 pages) :$$billustrations (some color).
000723351 336__ $$atext$$btxt$$2rdacontent
000723351 337__ $$acomputer$$bc$$2rdamedia
000723351 338__ $$aonline resource$$bcr$$2rdacarrier
000723351 4901_ $$aStudies in Big Data,$$x2197-6503 ;$$vvolume 7
000723351 504__ $$aIncludes bibliographical references and index.
000723351 5050_ $$aIntroduction -- Supervised Learning -- Unsupervised and Semi-supervised Learning -- Large-Scale Machine Learning.
000723351 506__ $$aAccess limited to authorized users.
000723351 520__ $$aThe overwhelming data produced everyday and the increasing performance and cost requirements of applications is transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data. This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind. It presents a series of new techniques to enhance, scale and distribute data in a Big Learning framework. It is not intended to be a comprehensive survey of the state of the art of the whole field of machine learning for Big Data. Its purpose is less ambitious and more practical: to explain and illustrate existing and novel GPU-based ML algorithms, not viewed as a universal solution for the Big Data challenges but rather as part of the answer, which may require the use of different strategies coupled together.
000723351 588__ $$aDescription based on online resource; title from PDF title page (SpringerLink, viewed July 7, 2014).
000723351 650_0 $$aMachine learning.
000723351 7001_ $$aRibeiro, Bernardete,$$eauthor.
000723351 77608 $$iPrint version:$$z9783319069371
000723351 830_0 $$aStudies in big data ;$$vv.7.
000723351 85280 $$bebk$$hSpringerLink
000723351 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-06938-8$$zOnline Access$$91397441.1
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000723351 980__ $$aEBOOK
000723351 980__ $$aBIB
000723351 982__ $$aEbook
000723351 983__ $$aOnline
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