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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
Languages
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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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Toc

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 AWS for deep learning

AWS is the biggest cloud provider, and so it deserves our attention. If you know how to use AWS and especially if you are familiar with spot requests, it can be a very cost-effective method to train complex deep learning models.

A brief introduction to AWS

This section gives you a brief introduction to how AWS works. It describes EC2, AMIs, and how to create a virtual machine in the cloud. This will not be an exhaustive introduction to AWS there are plenty of tutorials online that will guide you.

AWS is a suite of cloud resources. Another term for it is Infrastructure as a Service (IaaS), as opposed to Software as a Service (SaaS) or Platform as a Service (PaaS). In IaaS, as opposed to...

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