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 principlesSetting up your own deep-learning environmentImage classification and generationDeep 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

What is deep learning?Before we begin: the mathematical building blocks of neural networksGetting started with neural networksFundamentals of machine learning

PART 2 - DEEP LEARNING IN PRACTICE

Deep learning for computer visionDeep learning for text and sequencesAdvanced deep-learning best practicesGenerative deep learningConclusions