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035   $a(CKB)4330000002049883
035   $a(CaBNVSL)mat08327692
035   $a(IDAMS)0b00006487b95bf9
035   $a(IEEE)8327692
035   $a(OCoLC)1042908181$z(OCoLC)1088994598
035   $a(OCoLC-P)1042908181
035   $a(MaCbMITP)10654
035   $a(OCoLC)1042908181
035   $a(MdBmJHUP)muse70605
035   $a(MiAaPQ)EBC5340082
035   $a(oapen)https://directory.doabooks.org/handle/20.500.12854/78554
035   $a(PPN)254843506
035   $a(oapen)doab78554
035   $a(EXLCZ)994330000002049883
100   $a20180605d2018      uy         0
101 0 $aeng
135   $aur|n|||||||||
181   $2rdacontent
182   $2isbdmedia
183   $2rdacarrier
200 10$aMachine learning for data streams $ewith practical examples in MOA /$fAlbert Bifet, Ricard Gavalda?, Geoff Holmes, Bernhard Pfahringer
210   $aCambridge$cThe MIT Press$d2018
210  2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2018]
210  1$aCambridge, Massachusetts ; London, England$cThe MIT Press$d[2017]
215   $a1 PDF (xxi, 262 pages) $cillustrations
225 1 $aAdaptive computation and machine learning
311 08$a0-262-03779-3 
311 08$a0-262-34604-4 
320   $aIncludes bibliographical references and index.
330   $aA hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework.
410  0$aAdaptive computation and machine learning
606   $aDatabase management
606   $aNeural networks (Computer science)
606   $aMachine learning
615  0$aDatabase management.
615  0$aNeural networks (Computer science)
615  0$aMachine learning.
676   $a006.3/12
700   $aBifet$b Albert$01167471
702   $aGavalda?$b Ricard$f1964-
702   $aHolmes$b Geoffrey
702   $aPfahringer$b Bernhard
712 02$aMIT Press,
801  0$bOCoLC-P
801  1$bOCoLC-P
906   $aBOOK
912   $a9910524885703321
996   $aMachine Learning for Data Streams$92719505
997   $aUNINA