Also of great use was the section on validation and overfitting. These were easy enough to figure out and generalize to my problem. The examples in chapter 3 cover the most common cases: a binary classifier, a multiclass classifier and a regression problem. The best part about this book is hands-down the examples. I'll largely be reviewing the free chapters. just make your online documentation really good and save a book for the deep dive. The first three (and most important) chapters are free. Of course, one of the authors is the founder of RStudio and main author of the Keras library. This book fills a nice niche in that it is the only reliable reference for using the R interface to Keras. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras. No previous experience with machine learning or deep learning is assumed.įrançois Chollet is a deep-learning researcher at Google and the author of the Keras library. You'll need intermediate R programming skills. Setting up your own deep-learning environment You'll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples.
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. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks.ĭeep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. Machine learning has made remarkable progress in recent years. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. The book builds your understanding of deep learning through intuitive explanations and practical examples. Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface.
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