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TensorFlow 1.x Deep Learning Cookbook

You're reading from TensorFlow 1.x Deep Learning Cookbook Over 90 unique recipes to solve artificial-intelligence driven problems with Python

Product type Paperback

Published in Dec 2017

Publisher Packt

ISBN-13 9781788293594

Length 536 pages

Edition 1st Edition

Languages

Python

Tools

TensorFlow

Concepts

Deep Learning

Authors (2):

Dr. Amita Kapoor

Antonio Gulli

View More author details

Table of Contents (15) Chapters

Preface

1. TensorFlow - An Introduction FREE CHAPTER

2. Regression

3. Neural Networks - Perceptron

4. Convolutional Neural Networks

5. Advanced Convolutional Neural Networks

6. Recurrent Neural Networks

7. Unsupervised Learning

8. Autoencoders

9. Reinforcement Learning

10. Mobile Computation

11. Generative Models and CapsNet

12. Distributed TensorFlow and Cloud Deep Learning

13. Learning to Learn with AutoML (Meta-Learning)

14. TensorFlow Processing Units

Components of TPUs

Running Distributed TensorFlow on Microsoft Azure

Microsoft Azure offers a service called Batch AI that allows us to run our machine learning models on clusters of Azure virtual machines.

Getting ready

As the first step we need to have an Azure account: if you do not already have one, you can create one for free here: https://azure.microsoft.com/en-us/services/batch-ai/. The Azure offers $200 credit for 30 days to new users. This recipe will follow the example provided by Microsoft Azure to run MNIST on two GPUs using TensorFlow distributed, the relevant codes are available on Github: https://github.com/Azure/batch-shipyard/tree/master/recipes/TensorFlow-Distributed

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