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R Deep Learning Essentials

You're reading from   R Deep Learning Essentials A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781788992893
Length 378 pages
Edition 2nd Edition
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Authors (2):
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Joshua F. Wiley Joshua F. Wiley
Author Profile Icon Joshua F. Wiley
Joshua F. Wiley
Mark Hodnett Mark Hodnett
Author Profile Icon Mark Hodnett
Mark Hodnett
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Deep Learning 2. Training a Prediction Model FREE CHAPTER 3. Deep Learning Fundamentals 4. Training Deep Prediction Models 5. Image Classification Using Convolutional Neural Networks 6. Tuning and Optimizing Models 7. Natural Language Processing Using Deep Learning 8. Deep Learning Models Using TensorFlow in R 9. Anomaly Detection and Recommendation Systems 10. Running Deep Learning Models in the Cloud 11. The Next Level in Deep Learning 12. Other Books You May Enjoy

Using Google Cloud for deep learning

Google Cloud also has GPU instances. At the time of writing this book, the price of an instance with an NVIDIA Tesla K80 GPU card (which is also the GPU card in an AWS p2.xlarge instance) is $0.45 per hour on-demand. This is significantly cheaper than the AWS on-demand price. Further details of Google Cloud's GPU instances are at https://cloud.google.com/gpu/. However, for Google Cloud, we are not going to use instances. Instead, we are going to use the Google Cloud Machine Learning Engine API to submit machine learning jobs to the cloud. One big advantage of this approach over provisioning virtual machines is that you only pay for the hardware resources that you use and do not have to worry about setting up and terminating instances. More details and pricing can be found at https://cloud.google.com/ml-engine/pricing.

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