Deep learning : from big data to artificial intelligence with R / Stephane S. Tuffery.

By: Tuffery, Stephane [author.]
Language: English Original language: French Publisher: Chichester, West Sussex : John Wiley & Sons, Ltd, 2023Copyright date: 2023Description: 1 online resource (xix, 519 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119845010; 9781119845041; 1119845041; 9781119845027; 1119845025; 9781119845034; 1119845033Subject(s): Deep learning (Machine learning) | R (Computer program language) | Big data | Artificial intelligenceGenre/Form: Electronic books.DDC classification: 006.31 LOC classification: Q325.73 | .T84 2023Online resources: Full text is available at Wiley Online Library Click here to view
Contents:
Front 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.
Summary: DEEP 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.
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Item type Current location Home library Call number Status Date due Barcode Item holds
EBOOK EBOOK COLLEGE LIBRARY
COLLEGE LIBRARY
006.31 T815 2023 (Browse shelf) Available CL-51259
Total holds: 0

Translated from the French.

Includes bibliographical references and index.

Front 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.

DEEP 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.

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