Deep Learning with R

Deep Learning with R

<div><p><b>Summary</b></p> <p><i>Deep Learning with R</i> 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. </p> <p>Continue your journey into the world of deep learning with <i>Deep Learning with R in Motion</i>, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion).</p> <p>Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.</p> <p><b>About the Technology</b></p> <p>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.</p> <p><b>About the Book</b></p> <p><i>Deep Learning with R</i> 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.</p> <p><b>What's Inside</b></p> <p/><ul><li>Deep learning from first principles</li><li>Setting up your own deep-learning environment</li><li>Image classification and generation</li><li>Deep learning for text and sequences</li></ul> <p><b>About the Reader</b></p> <p>You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed.</p> <p><b>About the Authors</b></p> <p><b>François Chollet</b> is a deep-learning researcher at Google and the author of the Keras library.</p> <p><b>J.J. Allaire</b> is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras.</p> <p><b>Table of Contents</b></p> <p/><ol><h4>PART 1 - FUNDAMENTALS OF DEEP LEARNING</h4><li>What is deep learning?</li><li>Before we begin: the mathematical building blocks of neural networks</li><li>Getting started with neural networks</li><li>Fundamentals of machine learning</li><h4>PART 2 - DEEP LEARNING IN PRACTICE</h4><li>Deep learning for computer vision</li><li>Deep learning for text and sequences</li><li>Advanced deep-learning best practices</li><li>Generative deep learning</li><li>Conclusions</li> </ol></div>