Deep Learning with R

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

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 learningPART 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

Autorentext

Francois Chollet is a deep learning researcher at Google and the author of the Keras deep learning library. He blogs about deep learning at blog.keras.io.

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.

Klappentext

Key features

-+ Understand key machine learning concepts

-+ Set up a computer environment for deep learning

-+ Visualize neural networks

-+ Use recurrent neural networks for text and sequence Classification

Audience

YouGÇÖll need intermediate R programming skills. No previous experience with machine learning or deep learning is required.

Zusammenfassung

Key features

· Understand key machine learning concepts

· Set up a computer environment for deep learning

· Visualize neural networks

· Use recurrent neural networks for text and sequence Classification

Audience

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