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020 _a9789811358500
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024 7 _a10.1007/978-981-13-5850-0
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
_223
100 1 _aGhatak, Abhijit.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aDeep Learning with R
_h[electronic resource] /
_cby Abhijit Ghatak.
250 _a1st ed. 2019.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2019.
300 _aXXIII, 245 p. 100 illus., 83 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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505 0 _a Introduction to Machine Learning -- Introduction to Neural Networks -- Deep Neural Networks – I -- Initialization of Network Parameters -- Optimization -- Deep Neural Networks - II -- Convolutional Neural Networks (ConvNets) -- Recurrent Neural Networks (RNN) or Sequence Models -- Epilogue.
520 _aDeep Learning with R introduces deep learning and neural networks using the R programming language. The book builds on the understanding of the theoretical and mathematical constructs and enables the reader to create applications on computer vision, natural language processing and transfer learning. The book starts with an introduction to machine learning and moves on to describe the basic architecture, different activation functions, forward propagation, cross-entropy loss and backward propagation of a simple neural network. It goes on to create different code segments to construct deep neural networks. It discusses in detail the initialization of network parameters, optimization techniques, and some of the common issues surrounding neural networks such as dealing with NaNs and the vanishing/exploding gradient problem. Advanced variants of multilayered perceptrons namely, convolutional neural networks and sequence models are explained, followed by application to different use cases. The book makes extensive use of the Keras and TensorFlow frameworks. .
650 0 _aArtificial intelligence.
650 0 _aComputer science
_xMathematics.
650 0 _aComputer programming.
650 0 _aMathematical statistics
_xData processing.
650 1 4 _aArtificial Intelligence.
650 2 4 _aMathematics of Computing.
650 2 4 _aProgramming Techniques.
650 2 4 _aStatistics and Computing.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811358494
776 0 8 _iPrinted edition:
_z9789811358517
776 0 8 _iPrinted edition:
_z9789811370892
856 4 0 _uhttps://doi.org/10.1007/978-981-13-5850-0
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c185421
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