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001436083 001__ 1436083
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001436083 020__ $$a9789813365186$$q(electronic bk.)
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001436083 0247_ $$a10.1007/978-981-33-6518-6$$2doi
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001436083 049__ $$aISEA
001436083 050_4 $$aQ325.5
001436083 08204 $$a006.3/1$$223
001436083 24500 $$aMachine learning :$$btheoretical foundations and practical applications /$$cManjusha Pandey, Siddharth Swarup Rautaray, editors.
001436083 264_1 $$aSingapore :$$bSpringer,$$c[2021]
001436083 300__ $$a1 online resource (xi, 172 pages) :$$billustrations (some color).
001436083 336__ $$atext$$btxt$$2rdacontent
001436083 337__ $$acomputer$$bc$$2rdamedia
001436083 338__ $$aonline resource$$bcr$$2rdacarrier
001436083 4901_ $$aStudies in big data,$$x2197-6503 ;$$vvolume 87
001436083 5050_ $$aChapter 1. What do RDMs capture in Brain Responses and Computational Models? -- Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems -- Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification -- Chapter 4. Applications of Machine learning in industry 4.0 -- Chapter 5. Web Semantics and Knowledge Graph -- Chapter 6. Machine Learning based Wireless Sensor Networks -- Chapter 7. AI to Machine Learning:lifeless automation and Issues -- Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy -- Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.
001436083 506__ $$aAccess limited to authorized users.
001436083 520__ $$aThis edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.
001436083 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed April 28, 2021).
001436083 650_0 $$aMachine learning$$vCongresses.
001436083 650_6 $$aApprentissage automatique$$vCongrès.
001436083 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001436083 655_7 $$aConference papers and proceedings.$$2lcgft
001436083 655_7 $$aActes de congrès.$$2rvmgf
001436083 655_0 $$aElectronic books.
001436083 7001_ $$aPandey, Manjusha,$$eeditor.
001436083 7001_ $$aRautaray, Siddharth Swarup,$$eeditor.
001436083 77608 $$iPrint version: $$z981336517X$$z9789813365179$$w(OCoLC)1225976177
001436083 830_0 $$aStudies in big data ;$$vv. 87.$$x2197-6503
001436083 852__ $$bebk
001436083 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-33-6518-6$$zOnline Access$$91397441.1
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