LEADER 03744nam 22005415 450 001 9910337625903321 005 20200701173430.0 010 $a3-030-15729-6 024 7 $a10.1007/978-3-030-15729-6 035 $a(CKB)4100000008153844 035 $a(MiAaPQ)EBC5770988 035 $a(DE-He213)978-3-030-15729-6 035 $a(PPN)236525514 035 $a(EXLCZ)994100000008153844 100 $a20190507d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 13$aAn Introduction to Machine Learning /$fby Gopinath Rebala, Ajay Ravi, Sanjay Churiwala 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (275 pages) 311 $a3-030-15728-8 327 $aIntroduction -- Basics before Machine Learning -- Learning Models -- Regression -- Improving Further -- Classification -- Clustering (unsupervised Learning) -- Random Forests -- Testing the Algorithm and the Network -- Neural Network -- Reinforcement Learning -- Deep Learning -- Principal Component Analysis -- Anomaly Detection -- Recommender System -- Feature Search/Convolution -- Natural Language Processing -- Language Translation -- AlphaGo -- Data Quality -- System Improvement -- Software stack -- Hardware Implementations. . 330 $aJust like electricity, Machine Learning will revolutionize our life in many ways ? some of which are not even conceivable today. This book provides a thorough conceptual understanding of Machine Learning techniques and algorithms. Many of the mathematical concepts are explained in an intuitive manner. The book starts with an overview of machine learning and the underlying Mathematical and Statistical concepts before moving onto machine learning topics. It gradually builds up the depth, covering many of the present day machine learning algorithms, ending in Deep Learning and Reinforcement Learning algorithms. The book also covers some of the popular Machine Learning applications. The material in this book is agnostic to any specific programming language or hardware so that readers can try these concepts on whichever platforms they are already familiar with. Offers a comprehensive introduction to Machine Learning, while not assuming any prior knowledge of the topic; Provides a complete overview of available techniques and algorithms in conceptual terms, covering various application domains of machine learning; Not tied to any specific software language or hardware implementation. . 606 $aElectronic circuits 606 $aArtificial intelligence 606 $aComputational intelligence 606 $aCircuits and Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/T24068 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 615 0$aElectronic circuits. 615 0$aArtificial intelligence. 615 0$aComputational intelligence. 615 14$aCircuits and Systems. 615 24$aArtificial Intelligence. 615 24$aComputational Intelligence. 676 $a006.31 676 $a006.31 700 $aRebala$b Gopinath$4aut$4http://id.loc.gov/vocabulary/relators/aut$0862555 702 $aRavi$b Ajay$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aChuriwala$b Sanjay$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910337625903321 996 $aAn Introduction to Machine Learning$91925289 997 $aUNINA