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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

Playing with TensorFlow and Android examples

In this recipe, we will consider the standard Android examples presented in the TensorFlow distribution and install them on our mobile device.

Getting ready

TensorFlow mobile Android apps are available on GitHub at the following address: https://github.com/TensorFlow/TensorFlow/tree/master/TensorFlow/examples/android . In October 2017, the page contained the following examples:

TF Classify: Uses the Google Inception model to classify camera frames in real time, displaying the top results in an overlay on the camera image.
TF Detect: Demonstrates an SSD-Mobilenet model trained using the TensorFlow Object Detection API. This was introduced in speed/accuracy trade-offs for modern...

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