Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
Arrow right icon
View More author details
Toc

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...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image