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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

Profiling a TensorFlow graph for mobile devices

In this recipe, we will consider the different options to optimize TensorFlow code for running on a mobile device. Different options are analyzed, from reducing the size of the model to quantization.

Getting ready

We are going to use Bazel for building the different components of TensorFlow. Therefore, the first step is to make sure that both Bazel and TensorFlow are installed.

How to do it...

We proceed with profiling as follows:

Install Android Studio from https://developer.android.com/studio/install.html.

Install Bazel...

The rest of the chapter is locked

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