MARC Record from marc_columbia

LEADER: 03720cam a2200565 a 4500
001 13674578
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006 m o d
007 cr cnu---unuuu
008 170819s2017 ja ob 001 0 eng d
035 $a(OCoLC)on1001371602
035 $a(NNC)13674578
040 $aEBLCP$beng$epn$cEBLCP$dN$T$dTEFOD$dN$T$dTEFOD$dYDX$dIDEBK$dMERUC$dHCO$dOCLCQ$dVT2$dUOK$dOCLCF$dOTZ$dDKU$dWYU$dOCLCQ$dC6I$dZCU$dNRC$dUKAHL$dOCLCQ$dOCLCO$dOCLCQ
019 $a1000594260$a1264953144
020 $a9781491978481$q(electronic bk.)
020 $a1491978481$q(electronic bk.)
020 $a9781491978467$q(electronic bk.)
020 $a1491978465$q(electronic bk.)
020 $z9781491978511
020 $z1491978511
035 $a(OCoLC)1001371602$z(OCoLC)1000594260$z(OCoLC)1264953144
037 $a848FDD68-130F-44EC-B22E-C356ED217752$bOverDrive, Inc.$nhttp://www.overdrive.com
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082 04 $a006.31$223
049 $aZCUA
100 1 $aHope, Tom$c(Data scientist),$eauthor.
245 10 $aLearning TensorFlow :$ba guide to building deep learning systems /$cTom Hope, Yehezkel S. Resheff & Itay Lieder.
260 $aBeijing :$bO'Reilly,$c[2017]
300 $a1 online resource (240 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
588 0 $aOnline resource; title from PDF title page (EBSCO, viewed September 6, 2017).
520 $aRoughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience--from data scientists and engineers to students and researchers. You'll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems in TensorFlow.
500 $aIncludes index.
504 $aIncludes bibliographical references at the end of each chapters and index.
505 0 $aIntroduction -- Go with the flow : up and running with TensorFlow -- Understanding TensorFlow basics -- Convolution neural networks -- Text I : working with text and sequences, and TensorBoard visualization -- Text II : word vectors, advanced RNN, and embedding visualization -- TensorFlow abstractions and simplifications -- Queues, threads, and reading data -- Distributed TensorFlow -- Exporting and serving models with TensorFlow.
630 00 $aTensorFlow (Electronic resource)
650 0 $aMachine learning.
650 0 $aArtificial intelligence.
650 7 $aCOMPUTERS$xGeneral.$2bisacsh
650 7 $aArtificial intelligence.$2fast$0(OCoLC)fst00817247
650 7 $aMachine learning.$2fast$0(OCoLC)fst01004795
655 4 $aElectronic books.
700 1 $aResheff, Yehezkel S.,$eauthor.
700 1 $aLieder, Itay,$eauthor.
776 08 $iPrint version:$aHope, Tom (Data scientist).$tLearning TensorFlow.$dBeijing : O'Reilly, [2017]$z1491978511$z9781491978511$w(OCoLC)965492283
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio13674578$zAll EBSCO eBooks
852 8 $blweb$hEBOOKS