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Machine learning for big data analyis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning for big data analyis/ edited by Siddhartha Bhattacharyya ... [et al.].
其他作者:	Bhattacharyya, Siddhartha,
出版者:	Berlin ;De Gruyter, : c2019.,
面頁冊數:	1 online resource.
標題:	Big data. -
電子資源:	https://www.degruyter.com/isbn/9783110551433
ISBN:	9783110551433

Machine learning for big data analyis
Machine learning for big data analyis[electronic resource] /edited by Siddhartha Bhattacharyya ... [et al.]. - Berlin ;De Gruyter,c2019. - 1 online resource. - De Gruyter frontiers in computational intelligence,v. 12512-8868 ;. - De Gruyter frontiers in computational intelligence,v. 1..

Includes bibliographical references and index.

This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. 588

ISBN: 9783110551433

Standard No.: 10.1515/9783110551433doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Machine learning for big data analyis
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520 $a This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. 588 $a Description based on print version record.
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