LEADER 03442nam 2200529 450 001 9910260625403321 005 20230412220547.0 010 $a0-262-33760-6 035 $a(OCoLC)960457556 035 $a(CKB)3710000000891821 035 $a(MiAaPQ)EBC4714219 035 $a(CaBNVSL)mat07845169 035 $a(IDAMS)0b00006485bb822b 035 $a(IEEE)7845169 035 $a(PPN)220194084 035 $a(EXLCZ)993710000000891821 100 $a20170308d2016 uy 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aMachine learning $ethe new AI /$fEthemAlpaydin 210 1$aCambridge, Massachusetts :$cThe MIT Press,$d[2016] 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2016] 215 $a1 online resource (225 pages) $cillustrations 225 1 $aThe mit press essential knowledge series 225 1 $aMIT Press essential knowledge series 311 $a0-262-52951-3 311 $a0-262-33759-2 320 $aIncludes bibliographical references and index. 327 $aWhy we are interested in machine learning -- Machine learning, statistics and data analytics -- Pattern recognition -- Neural networks and deep learning -- Learning clusters and recommendations -- Learning to take actions -- Where do we go from here? 330 $aToday, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition -- as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as "Big Data" has gotten bigger, the theory of machine learning -- the foundation of efforts to process that data into knowledge -- has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of "data science," and discusses the ethical and legal implications for data privacy and security. 410 0$aMIT Press essential knowledge series. 606 $aMachine learning 606 $aArtificial intelligence 615 0$aMachine learning. 615 0$aArtificial intelligence. 676 $a006.31 700 $aAlpaydin$b Ethem$0754614 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910260625403321 996 $aMachine learning$91756221 997 $aUNINA