000 04237cam a2200505 i 4500
999 _c88874
_d88874
003 CITU
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006 m o d
007 cr |n|||||||||
008 241001b ||||| |||| 00| 0 eng d
020 _a9781119845010
_qhardcover
020 _a9781119845041
_q(electronic bk. : oBook)
020 _a1119845041
_q(electronic bk. : oBook)
020 _a9781119845027
_qelectronic book
020 _a1119845025
_qelectronic book
020 _a9781119845034
_q(electronic bk.)
020 _a1119845033
_q(electronic bk.)
020 _z1119845017
_qhardcover
024 7 _a10.1002/9781119845041
_2doi
035 _a(OCoLC)1350684170
037 _a9968098
_bIEEE
040 _aYDX
_beng
_erda
_cYDX
_dYDX
_dDG1
_dIEEEE
_dOCLCF
041 1 _aeng
_hfre
050 4 _aQ325.73
_b.T84 2023
082 0 4 _a006.31
_223
100 1 _aTuffery, Stephane,
_0https://id.loc.gov/authorities/names/no2009138627
_eauthor.
245 1 0 _aDeep learning :
_bfrom big data to artificial intelligence with R /
_cStephane S. Tuffery.
264 1 _aChichester, West Sussex :
_bJohn Wiley & Sons, Ltd,
_c2023.
264 4 _c2023.
300 _a1 online resource (xix, 519 pages) :
_billustrations (some color)
336 _atext
_btxt
_2rdacontent.
337 _acomputer
_bc
_2rdamedia.
338 _aonline resource
_bcr
_2rdacarrier.
500 _aTranslated from the French.
504 _aIncludes bibliographical references and index.
505 0 _aFront Matter -- From Big Data to Deep Learning -- Processing of Large Volumes of Data -- Reminders of Machine Learning -- Natural Language Processing -- Social Network Analysis -- Handwriting Recognition -- Deep Learning -- Deep Learning for Computer Vision -- Deep Learning for Natural Language Processing -- Artificial Intelligence -- Conclusion -- Annotated Bibliography -- Index.
520 _aDEEP LEARNING A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. St�ephane Tuff�ery delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on various software tools and deep learning methods relying on three major libraries: MXNet, PyTorch, and Keras-TensorFlow. In the book, numerous, up-to-date examples are combined with key topics relevant to modern data scientists, including processing optimization, neural network applications, natural language processing, and image recognition. This is a thoroughly revised and updated edition of a book originally released in French, with new examples and methods included throughout. Classroom-tested and intuitively organized, Deep Learning: From Big Data to Artificial Intelligence with R offers complimentary access to a companion website that provides R and Python source code for the examples offered in the book. Readers will also find: A thorough introduction to practical deep learning techniques with explanations and examples for various programming libraries Comprehensive explorations of a variety of applications for deep learning, including image recognition and natural language processing Discussions of the theory of deep learning, neural networks, and artificial intelligence linked to concrete techniques and strategies commonly used to solve real-world problems Perfect for graduate students studying data science, big data, deep learning, and artificial intelligence, Deep Learning: From Big Data to Artificial Intelligence with R will also earn a place in the libraries of data science researchers and practicing data scientists.
650 0 _aDeep learning (Machine learning)
_0https://id.loc.gov/authorities/subjects/sh2021006947.
650 0 _aR (Computer program language)
_0https://id.loc.gov/authorities/subjects/sh2002004407.
650 0 _aBig data.
_0https://id.loc.gov/authorities/subjects/sh2012003227.
650 0 _aArtificial intelligence.
_0https://id.loc.gov/authorities/subjects/sh85008180.
655 4 _aElectronic books.
856 4 0 _uhttps://onlinelibrary.wiley.com/doi/book/10.1002/9781119845041
_yFull text is available at Wiley Online Library Click here to view
942 _2ddc
_cER