Francois Chollet 
Deep Learning with R [EPUB ebook] 

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 e Book in PDF, Kindle, and e Pub 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 Franois 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 Franois 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 Tensor Flow and Keras.Table of Contents PART 1 — FUNDAMENTALS OF DEEP LEARNINGWhat is deep learning?Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 — DEEP LEARNING IN PRACTICEDeep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions