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020 _a9789811085697
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024 7 _a10.1007/978-981-10-8569-7
_2doi
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_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
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082 0 4 _a006.3
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245 1 0 _aAdvances in Machine Learning and Data Science
_h[electronic resource] :
_bRecent Achievements and Research Directives /
_cedited by Damodar Reddy Edla, Pawan Lingras, Venkatanareshbabu K.
250 _a1st ed. 2018.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2018.
300 _aXII, 380 p. 157 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Intelligent Systems and Computing,
_x2194-5365 ;
_v705
505 0 _aPreface -- About the Editors -- Table of Contents -- 38 Papers -- Author Index.
520 _aThe Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms. .
650 0 _aComputational intelligence.
_97716
650 0 _aData mining.
_93907
650 0 _aBig data.
_94174
650 0 _aQuantitative research.
_94633
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aData Mining and Knowledge Discovery.
_951896
650 2 4 _aBig Data.
_94174
650 2 4 _aData Analysis and Big Data.
_951897
700 1 _aReddy Edla, Damodar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_951898
700 1 _aLingras, Pawan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_951899
700 1 _aVenkatanareshbabu K.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_951900
710 2 _aSpringerLink (Online service)
_951901
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811085680
776 0 8 _iPrinted edition:
_z9789811085703
830 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5365 ;
_v705
_951902
856 4 0 _uhttps://doi.org/10.1007/978-981-10-8569-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
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