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Intelligent Mobile Projects with TensorFlow

You're reading from   Intelligent Mobile Projects with TensorFlow Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
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Author (1):
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Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Mobile TensorFlow FREE CHAPTER 2. Classifying Images with Transfer Learning 3. Detecting Objects and Their Locations 4. Transforming Pictures with Amazing Art Styles 5. Understanding Simple Speech Commands 6. Describing Images in Natural Language 7. Recognizing Drawing with CNN and LSTM 8. Predicting Stock Price with RNN 9. Generating and Enhancing Images with GAN 10. Building an AlphaZero-like Mobile Game App 11. Using TensorFlow Lite and Core ML on Mobile 12. Developing TensorFlow Apps on Raspberry Pi 13. Other Books You May Enjoy

Setting up TensorFlow on Raspberry Pi

To use TensorFlow in Python, as we'll do in the Audio recognition and Reinforcement learning sections later, we can install the TensorFlow 1.6 nightly build for Pi at the TensorFlow Jenkins continuous integrate site (http://ci.tensorflow.org/view/Nightly/job/nightly-pi/223/artifact/output-artifacts):

sudo pip install http://ci.tensorflow.org/view/Nightly/job/nightly-pi/lastSuccessfulBuild/artifact/output-artifacts/tensorflow-1.6.0-cp27-none-any.whl

This method is more common and described in detail in a nice blog entry, Cross-compiling TensorFlow for the Raspberry Pi (https://petewarden.com/2017/08/20/cross-compiling-tensorflow-for-the-raspberry-pi), by Pete Warden.

A more complicated method is to use the makefile, required when you need to build and use the TensorFlow library. The Raspberry Pi section of the official TensorFlow makefile...

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