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Autor(en): 
  • Joseph J Allaire
  • Joseph Allaire
  • Deep Learning with R 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  April 2018  
    Genre:  EDV / Informatik 
    ISBN:  9781617295546 
    EAN-Code: 
    9781617295546 
    Verlag:  Pearson Academic 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Pearson  
    Dimensionen:  H 235 mm / B 185 mm / D 20 mm 
    Gewicht:  680 gr 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Summary

    Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples.

    Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion).

    Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

    About the Technology

    Machine learning has made remarkable progress in recent years. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks.

    About the Book

    Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStudio founder J. J. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples. You'll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models.

    What's Inside

    • Deep learning from first principles
    • Setting up your own deep-learning environment
    • Image classification and generation
    • Deep learning for text and sequences

    About the Reader

    You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed.

    About the Authors

    François Chollet is a deep-learning researcher at Google and the author of the Keras library.

    J.J. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras.

    Table of Contents

      PART 1 - FUNDAMENTALS OF DEEP LEARNING

    1. What is deep learning?
    2. Before we begin: the mathematical building blocks of neural networks
    3. Getting started with neural networks
    4. Fundamentals of machine learning
    5. PART 2 - DEEP LEARNING IN PRACTICE

    6. Deep learning for computer vision
    7. Deep learning for text and sequences
    8. Advanced deep-learning best practices
    9. Generative deep learning
    10. Conclusions

      
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