LEADER 02369oam 2200421 450 001 9910484871303321 005 20230912093759.0 010 $a981-336-518-8 035 $a(OCoLC)1248737592 035 $a(MiFhGG)GVRL573D 035 $a(EXLCZ)994100000011891400 100 $a20230905h20212021 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aMachine learning $etheoretical foundations and practical applications /$fManjusha Pandey, Siddharth Swarup Rautaray, editors 210 1$aSingapore :$cSpringer,$d[2021] 210 4$dİ2021 215 $a1 online resource (xi, 172 pages) $cillustrations (some color), charts 225 1 $aStudies in Big Data ;$vv.87 311 $a981-336-517-X 320 $aIncludes bibliographical references. 327 $aWhat do RDMs capture in brain responses and computational models? -- Challenges and solutions in developing convolutional neural networks and long short-term memory networks for industry problems -- Speed, cloth and pose invariant gait recognition-based person identification -- Application of machine learning in industry 4.0 -- Web semantics and knowledge graph -- Machine learning-based wireless sensor networks -- AI to machine learning : lifeless automation and issues -- Analysis of FDIs in different sectors of the Indian economy -- Customer profiling and retention using recommendation system and factor identification to predict customer churn in telecom industry. 330 $aTopics include neural network learning, knowledge acquisition and learning, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms. 410 0$aStudies in big data ;$vv. 87. 606 $aMachine learning 615 0$aMachine learning. 676 $a006.31 702 $aPandey$b Manjusha 702 $aRautaray$b Siddharth Swarup 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910484871303321 996 $aMachine learning$9257234 997 $aUNINA