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Deep Learning with R
Contributor(s): Chollet, Francois (Author), Allaire, J. J. (As Told to)
ISBN: 161729554X     ISBN-13: 9781617295546
Publisher: Manning Publications
OUR PRICE:   $47.49  
Product Type: Paperback - Other Formats
Published: February 2018
Qty:
Additional Information
BISAC Categories:
- Computers | Neural Networks
- Computers | Natural Language Processing
- Computers | Machine Theory
Dewey: 005.133
LCCN: 2018285360
Physical Information: 0.75" H x 7.38" W x 9.25" (1.40 lbs) 360 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
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 Fran ois 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

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

Contributor Bio(s): Chollet, Francois: -

Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io.

Allaire, J. J.: -

J.J. Allaire is the Founder of RStudio and the creator of the RStudio IDE. J.J. is the author of the R interfaces to TensorFlow and Keras.