Book Image

Intelligent Mobile Projects with TensorFlow

By : Jeff Tang
Book Image

Intelligent Mobile Projects with TensorFlow

By: Jeff Tang

Overview of this book

As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You’ll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips.
Table of Contents (14 chapters)

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...