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Look inside
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.
If you’re looking to dig further into deep learning, then Deep Learning with R in Motion is the perfect next step. This video course offers more examples, exercises, and skills to help you lock in what you learn!
This book is included in the
Deep Learning with R and
Getting Started with R Deep Learning bundles.
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.
The clearest explanation of deep learning I have come across...it was a joy to read.
An excellent hands-on introductory title, with great depth and breadth.
Bridges the gap between the hype and a functioning deep-learning system.
All major topics and concepts of deep learning are covered and well explained, using code examples and diagrams instead of mathematical formulas.
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