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Deep Learning with R, Second Edition

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$156.00
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Description

Deep learning from the ground up using R and the powerful Keras library! In   Deep Learning with R, Second Edition  you will learn: Deep learning from first principles Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation Deep Learning with R, Second Edition  shows you how to put deep learning into action. It's based on the revised new edition of François Chollet's bestselling   Deep Learning with Python. All code and examples have been expertly translated to the R language by Tomasz Kalinowski, who maintains the Keras and Tensorflow R packages at RStudio. Novices and experienced ML practitioners will love the expert insights, practical techniques, and important theory for building neural networks. about the technology Deep learning has become essential knowledge for data scientists, researchers, and software developers. The R language APIs for Keras and TensorFlow put deep learning within reach for all R users, even if they have no experience with advanced machine learning or neural networks. This book shows you how to get started on core DL tasks like computer vision, natural language processing, and more using R. what's inside Image classification and image segmentation Time series forecasting Text classification and machine translation Text generation, neural style transfer, and image generation about the reader For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.  

Author Biography:

François Chollet  is a software engineer at Google and creator of Keras.  Tomasz Kalinowski  is a software engineer at RStudio and maintainer of the Keras and Tensorflow R packages.  J.J. Allaire  is the founder of RStudio, and the author of the first edition of this book.
Release date NZ
August 3rd, 2022
Pages
568
Edition
2nd edition
Audience
  • Professional & Vocational
Dimensions
186x234x32
ISBN-13
9781633439849
Product ID
35866365

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