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Machine learning for big data analysis

Machine learning for big data analysis
Kataloginformation
Feldname Details
Vorliegende Sprache eng
URL https://doi.org/10.1515/9783110551433
https://www.gbv.de/dms/bowker/toc/9783110550320.pdf
https://www.degruyter.com/doc/cover/9783110551433.jpg
https://zbmath.org/?q=an:1405.68004
https://www.degruyter.com/cover/covers/9783110551433.jpg
Name Bhattacharyya, Siddhartha ˜[HerausgeberIn]œ
Bhaumik, Hrishikesh ˜[HerausgeberIn]œ
Mukherjee, Anirban ˜[HerausgeberIn]œ
De, Sourav ˜[HerausgeberIn]œ
T I T E L Machine learning for big data analysis
Verfasserangabe edited by Siddhartha Bhattacharyya, Hrishikesh Bhaumik, Anirban Mukherjee, Sourav De
Verlagsort Berlin ; Boston
Verlag De Gruyter
Erscheinungsjahr [2019]
Umfang 1 Online-Ressource (183 Seiten)
Reihe De Gruyter frontiers in computational intelligence
Band Volume 1
Titelhinweis Erscheint auch als (Druckausgabe): ‡Machine learning for big data analysis
ISBN ISBN 978-3-11-055077-1 EPUB
ISBN 978-3-11-055143-3 PDF
Kurzbeschreibung 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. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent research.
1. Schlagwort Big Data
Datenanalyse
Maschinelles Lernen
2. Schlagwort Big Data
Data Science
SWB-Titel-Idn 506131343
Kataloginformation334590378 Datensatzanfang . Kataloginformation334590378 Seitenanfang .
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