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Machine Learning for Mobile

You're reading from   Machine Learning for Mobile Practical guide to building intelligent mobile applications powered by machine learning

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781788629355
Length 274 pages
Edition 1st Edition
Tools
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Authors (2):
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Avinash Venkateswarlu Avinash Venkateswarlu
Author Profile Icon Avinash Venkateswarlu
Avinash Venkateswarlu
Revathi Gopalakrishnan Revathi Gopalakrishnan
Author Profile Icon Revathi Gopalakrishnan
Revathi Gopalakrishnan
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to Machine Learning on Mobile FREE CHAPTER 2. Supervised and Unsupervised Learning Algorithms 3. Random Forest on iOS 4. TensorFlow Mobile in Android 5. Regression Using Core ML in iOS 6. The ML Kit SDK 7. Spam Message Detection 8. Fritz 9. Neural Networks on Mobile 10. Mobile Application Using Google Vision 11. The Future of ML on Mobile Applications 12. Question and Answers 13. Other Books You May Enjoy

An introduction to TensorFlow

TensorFlow is a tool to implement machine learning developed by Google, and was open sourced in 2015. It is a product that can be installed on desktops and can be used to create machine learning models. Once the model has been built and trained on the desktop, the developer can transfer these models to mobile devices and start using them to predict results in mobile applications by integrating them into iOS and Android mobile applications. There are currently two flavors of TensorFlow available for implementing machine learning solutions on mobile and embedded devices:

  • Mobile devices: TensorFlow for Mobile
  • Mobile and Embedded devices: TensorFlow Lite 

The following table will help you to understand the key differences between TensorFlow for mobile and TensorFlow Lite:

TensorFlow for Mobile

TensorFlow Lite

Designed to...

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