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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

Summary

In this chapter, we covered two cutting-edge tools of using machine learning and deep learning models on mobile and embedded devices: TensorFlow Lite and Core ML. While TensorFlow Lite is still in developer preview, with limited support for TensorFlow operations, its future releases will support more and more TensorFlow features, while keeping the latency low and app size small. We offered step-by-step tutorials on how to develop TensorFlow Lite iOS and Android apps to classify an image from scratch. Core ML is Apple's framework for mobile developers to integrate machine learning in iOS apps, and it has great support for converting and using classical machine learning models built with Scikit Learn, as well as good support for Keras-based models. We also showed how to convert Scikit Learn and Keras models to Core ML models and use them in Objective-C and Swift apps...

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