| Record ID | marc_openlibraries_sanfranciscopubliclibrary/sfpl_chq_2018_12_24_run05.mrc:426491588:3692 |
| Source | marc_openlibraries_sanfranciscopubliclibrary |
| Download Link | /show-records/marc_openlibraries_sanfranciscopubliclibrary/sfpl_chq_2018_12_24_run05.mrc:426491588:3692?format=raw |
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003 OCoLC
005 20171121090522.0
008 150202s2017 caua b 001 0 eng d
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020 $a1491914254
020 $a9781491914250
035 $a(OCoLC)902657832$z(OCoLC)902660112$z(OCoLC)907092057
037 $bOreilly & Associates Inc, C/O Ingram Pub Services 1 Ingram Blvd, LA Vergne, TN, USA, 37086$nSAN 631-8673
040 $aYDXCP$beng$erda$cYDXCP$dOCLCQ$dBDX$dBTCTA$dOCLCQ$dGK8$dSINLB$dOCLCO$dFM0$dJED$dNZWPM$dDAC$dOCLCF$dSFR$dUtOrBLW
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050 14 $aQA325.5$b.P38 2017
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100 1 $aPatterson, Josh$c(Consultant),$eauthor.
245 10 $aDeep learning :$ba practitioner's approach /$cJosh Patterson and Adam Gibson.
250 $aFirst edition.
264 1 $aSebastopol, CA :$bO'Reilly,$c2017.
300 $axxi, 507 pages :$billustrations ;$c24 cm
336 $atext$btxt$2rdacontent
337 $aunmediated$bn$2rdamedia
338 $avolume$bnc$2rdacarrier
504 $aIncludes bibliographical references and index.
505 0 $aA review of machine learning -- Foundations of neural networks and deep learning -- Fundamentals of deep networks -- Major architecture of deep networks -- Building deep networks -- Tuning deep networks -- Tuning specific deep network architectures -- Vectorization -- Using deep learning and DL4J on Spark -- What is artificial intelligence? -- RL4J and reinforcement learning -- Numbers everyone should know -- Neural networks and backpropagation: a mathematical approach -- Using the ND4J API -- Using DataVec -- Working with DL4J from source -- Setting up DL4J projects -- Setting up GPUs for DL4J projects -- Troubleshooting DL4J installations.
520 $aHow can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, parallelization, vectorization, and building pipelines--that are valid for any library before introducing the open source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you'll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.
650 0 $aMachine learning.
650 0 $aNeural networks (Computer science)
650 0 $aOpen source software.
700 1 $aGibson, Adam,$eauthor.
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938 $aYBP Library Services$bYANK$n12270353
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