October 2022
15h 37m
English
audiobook
Deep Learning with R, Second Edition
by Francois Chollet, Sigrid Keydana, Tomasz Kalinowski, J.J. Allaire
Overview
Deep learning from the ground up using R and the powerful Keras library!
In Deep Learning with R, Second Edition you will learn:
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.
About the Book
Deep Learning with R, Second Edition is a hands-on guide to deep learning using the R language. As you move through this book, you’ll quickly lock in the foundational ideas of deep learning. The intuitive explanations, crisp illustrations, and clear examples guide you through core DL skills like image processing and text manipulation, and even advanced features like transformers. This revised and expanded new edition is adapted from Deep Learning with Python, Second Edition by François Chollet, the creator of the Keras library.
What's Inside
About the Reader
For readers with intermediate R skills. No previous experience with Keras, TensorFlow, or deep learning is required.
About the Authors
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.
Quotes
A must-have for scientists and technicians who want to expand their knowledge.
- Fernando García Sedano, Grupo Epelsa
Whether you are new to deep learning or wanting to expand your applications in R, there is no better guide.
- Michael Petrey, Boxplot Analytics
The clear illustrations and insightful examples are helpful to anybody, from beginners to experienced deep learning practitioners.
- Edward Lee, Yale University
Outstandingly well written.
- Shahnawaz Ali, King’s College London
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
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.
About the Book
Deep Learning with R, Second Edition is a hands-on guide to deep learning using the R language. As you move through this book, you’ll quickly lock in the foundational ideas of deep learning. The intuitive explanations, crisp illustrations, and clear examples guide you through core DL skills like image processing and text manipulation, and even advanced features like transformers. This revised and expanded new edition is adapted from Deep Learning with Python, Second Edition by François Chollet, the creator of the Keras library.
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.
About the Authors
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.
Quotes
A must-have for scientists and technicians who want to expand their knowledge.
- Fernando García Sedano, Grupo Epelsa
Whether you are new to deep learning or wanting to expand your applications in R, there is no better guide.
- Michael Petrey, Boxplot Analytics
The clear illustrations and insightful examples are helpful to anybody, from beginners to experienced deep learning practitioners.
- Edward Lee, Yale University
Outstandingly well written.
- Shahnawaz Ali, King’s College London
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