Deep Learning with R

Book 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.

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

About the

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 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├žois 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 vision, natural-language processing, and generative .

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 skills. No previous experience with machine learning or deep learning is assumed.

About the Authors

Fran├žois 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
Chapter 1. What Is Deep Learning?
Chapter Before We Begin: The Mathematical Building Blocks Of Neural Networks
Chapter Getting Started With Neural Networks
Chapter Fundamentals Of Machine Learning

PART 2 - DEEP LEARNING IN PRACTICE
Chapter 1. Deep Learning For Computer Vision
Chapter 2. Deep Learning For Text And Sequences
Chapter 3. Advanced Deep-Learning Best Practices
Chapter 4. Generative Deep Learning
Chapter 5. Conclusions

Book Details

Book Link

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Download from NitroFlarePDF (convert), EPUB25.705/02/2019
Download from UsersCloudPDF(convert)16.807/12/2018
Download from UsersCloudPDF (convert), EPUB25.705/02/2019
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