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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

Working with TensorFlow Serving and Docker

In this recipe we will show how to run a Docker container for TensorFlow Serving, a set of components to export a trained TensorFlow model and use the standard tensorflow_model_server to serve it. The TensorFlow Serving server discovers new exported models and runs a gRPC service for serving them.

Getting ready

We will use Docker and will assume that you are familiar with the system. If not, please make sure that you have a look to https://www.docker.com/ and install it. What we are going to do is to build a version of TF Serving.

How to do it...

...

The rest of the chapter is locked

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