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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

2. Regression FREE CHAPTER

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 Google CloudML

CloudML is a managed version of Tensorflow run by Google. Instead of running TF by yourself you can simply use CloudML and forget all the issues related to infrastructure and scalability.

Getting ready

Here we assume that you have already created a Cloud Platform Project, enabling billing for your project, and enable the Google Compute Engine and the Cloud Machine Learning APIs. These steps are similar to the ones described in the previous recipes. This recipe is inspired by the MNIST training code available in https://cloud.google.com/ml-engine/docs/distributed-tensorflow-mnist-cloud-datalab.

...

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