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Mastering TensorFlow 1.x

You're reading from Mastering TensorFlow 1.x Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Product type Paperback

Published in Jan 2018

Publisher Packt

ISBN-13 9781788292061

Length 474 pages

Edition 1st Edition

Languages

Python

Tools

Keras

Concepts

Deep Learning

Table of Contents (26) Chapters

Title Page

Copyright and Credits

Packt Upsell

Foreword

Contributors

Preface

1. TensorFlow 101

2. High-Level Libraries for TensorFlow FREE CHAPTER

3. Keras 101

4. Classical Machine Learning with TensorFlow

5. Neural Networks and MLP with TensorFlow and Keras

6. RNN with TensorFlow and Keras

7. RNN for Time Series Data with TensorFlow and Keras

8. RNN for Text Data with TensorFlow and Keras

9. CNN with TensorFlow and Keras

10. Autoencoder with TensorFlow and Keras

11. TensorFlow Models in Production with TF Serving

12. Transfer Learning and Pre-Trained Models

13. Deep Reinforcement Learning

14. Generative Adversarial Networks

15. Distributed Models with TensorFlow Clusters

16. TensorFlow Models on Mobile and Embedded Platforms

17. TensorFlow and Keras in R

18. Debugging TensorFlow Models

19. Tensor Processing Units

1. Other Books You May Enjoy

Leave a review - let other readers know what you think

TF Lite demo on iOS

In order to build the demo on iOS, you need Xcode 7.3 or later. Follow these steps to build the iOS demo apps:

Check out the TensorFlow code in a tensorflow folder in your home directory.
Build the TF Lite binary for iOS from the instructions at this link: https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite.
Navigate to the sample folder and download the pod:

$ cd ~/tensorflow/tensorflow/contrib/lite/examples/ios/camera
$ pod install

Open the Xcode workspace:

$ open tflite_camera_example.xcworkspace

Run the sample app in the device simulator.

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