MARC Record from marc_columbia

LEADER: 05370cam a2200925 i 4500
001 15774821
005 20220521232935.0
006 m o d
007 cr cnu---unuuu
008 211007s2022 flu ob 001 0 eng d
035 $a(OCoLC)on1273732695
035 $a(NNC)15774821
040 $aTYFRS$beng$erda$epn$cTYFRS$dOCLCF$dTYFRS$dYDX$dN$T$dOCLCQ$dOCLCO
019 $a1282594155$a1283139143$a1283821153
020 $a9781003206743$q(electronic bk.)
020 $a1003206743$q(electronic bk.)
020 $a9781000450477$q(electronic bk. ;$qEPUB)
020 $a1000450473$q(electronic bk. ;$qEPUB)
020 $a9781000450415$q(electronic bk. ;$qPDF)
020 $a1000450414$q(electronic bk. ;$qPDF)
020 $z9780367768584
020 $z0367768585
020 $z9781032074016
020 $z1032074019
035 $a(OCoLC)1273732695$z(OCoLC)1282594155$z(OCoLC)1283139143$z(OCoLC)1283821153
037 $a9781003206743$bTaylor & Francis
050 4 $aQC52$b.R38 2022eb
072 7 $aCOM$x021030$2bisacsh
072 7 $aCOM$x037000$2bisacsh
072 7 $aSCI$x055000$2bisacsh
072 7 $aPH$2bicssc
082 04 $a530.0285/53$223
049 $aZCUA
100 1 $aRauf, Ijaz A.,$eauthor.
245 10 $aPhysics of data science and machine learning /$cIjaz A. Rauf.
250 $aFirst edition.
264 1 $aBoca Raton :$bCRC Press,$c2022.
300 $a1 online resource
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
504 $aIncludes bibliographical references and index.
505 0 $aAn overview of classical mechanics -- An overview of quantum mechanics -- Probabilistic physics -- Design of experiments and analyses -- Basics of machine learning -- Prediction, optimization, and new knowledge development.
520 $a"Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, whilst exploring neural networks and machine learning building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid the development of new and innovative machine learning and artificial intelligence tools. Key features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations, instead equations are presented and explained strategically and explain why"--$cProvided by publisher
545 0 $aIjaz A. Rauf is Adjunct Professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an Associate Researcher at Ryerson University, Toronto, Canada and President of the Eminent-Tech Corporation, Bradford, ON, Canada.
588 0 $aPrint version record.
650 0 $aPhysics$xData processing.
650 0 $aPhysics$xMethodology.
650 0 $aMachine learning.
650 0 $aData mining.
650 0 $aStatistical mechanics.
650 0 $aQuantum statistics.
650 0 $aProbabilities.
650 0 $aMathematical optimization.
650 2 $aData Mining
650 2 $aProbability
650 6 $aPhysique$xInformatique.
650 6 $aPhysique$xMéthodologie.
650 6 $aApprentissage automatique.
650 6 $aExploration de données (Informatique)
650 6 $aMécanique statistique.
650 6 $aStatistique quantique.
650 6 $aProbabilités.
650 6 $aOptimisation mathématique.
650 7 $aprobability.$2aat
650 7 $aCOMPUTERS$xDatabase Management$xData Mining.$2bisacsh
650 7 $aCOMPUTERS$xMachine Theory.$2bisacsh
650 7 $aSCIENCE$xPhysics.$2bisacsh
650 7 $aData mining.$2fast$0(OCoLC)fst00887946
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
650 7 $aMathematical optimization.$2fast$0(OCoLC)fst01012099
650 7 $aPhysics$xData processing.$2fast$0(OCoLC)fst01063041
650 7 $aPhysics$xMethodology.$2fast$0(OCoLC)fst01063075
650 7 $aProbabilities.$2fast$0(OCoLC)fst01077737
650 7 $aQuantum statistics.$2fast$0(OCoLC)fst01085127
650 7 $aStatistical mechanics.$2fast$0(OCoLC)fst01132070
655 4 $aElectronic books.
776 08 $iPrint version:$aRauf, Ijaz A.$tPhysics of data science and machine learning.$bFirst edition.$dBoca Raton : CRC Press, 2022$z9780367768584$w(DLC) 2021023415$w(OCoLC)1268122074
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15774821$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS