
Deep Learning with R, Second Edition
Manning Publications (Publisher)
2nd Edition
Published on 3. August 2022
Book
Paperback/Softback
568 pages
978-1-63343-984-9 (ISBN)
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 Francois 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.
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 Francois 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.
More details
Edition
2nd edition
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 232 mm
Width: 186 mm
Thickness: 31 mm
Weight
856 gr
ISBN-13
978-1-63343-984-9 (9781633439849)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition

Joseph Allaire
Deep Learning with R
Book
04/2018
Manning Publications
€47.00
Shipment within 10-20 days
Persons
Francois 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.