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Machine Learning for Mobile

You're reading from Machine Learning for Mobile

Product type Book

Published in Dec 2018

Publisher Packt

ISBN-13 9781788629355

Pages 274 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Revathi Gopalakrishnan

Avinash Venkateswarlu

View More author details

Table of Contents (19) Chapters

Title Page

Copyright and Credits

About Packt

Contributors

Preface

1. Introduction to Machine Learning on Mobile

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

1. Question and Answers

2. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Understanding ML Kit

ML Kit encompasses all the existing Google offerings for machine learning on mobile. It bundles the Google Cloud Vision API, TensorFlow Lite, and the Android Neural Networks API together in a single SDK, as shown:

ML Kit enables developers to utilize machine learning in their mobile applications for both Android and iOS apps, in a very easy way. Inference can be carried out by invoking APIs that are either on-device or on-cloud.

The advantages of on-device APIs are that they work completely offline, and are more secure as no data is sent to the cloud. By contrast, on-cloud APIs do require network connectivity, and do send data off-device, but allow for greater accuracy.

ML Kit offers APIs covering the following machine learning scenarios that may be required by mobile application developers:

Image labeling
Text recognition
Landmark detection
Face detection
Barcode scanning

All these APIs are implemented using complex machine learning algorithms. However, those details are wrapped...

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Authors (2)

Revathi Gopalakrishnan

Revathi Gopalakrishnan is a software professional with more than 17 years of experience in the IT industry. She has worked extensively in mobile application development and has played various roles, including developer and architect, and has led various enterprise mobile enablement initiatives for large organizations. She has also worked on a host of consumer applications for various customers around the globe. She has an interest in emerging areas, and machine learning is one of them. Through this book, she has tried to bring out how machine learning can make mobile application development more interesting and super cool. Revathi resides in Chennai and enjoys her weekends with her husband and her two lovely daughters.

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See other products by Revathi Gopalakrishnan

Avinash Venkateswarlu

Avinash Venkateswarlu has more than 3 years' experience in IT and is currently exploring mobile machine learning. He has worked in enterprise mobile enablement projects and is interested in emerging technologies such as mobile machine learning and cryptocurrency. Venkateswarlu works in Chennai, but enjoys spending his weekends in his home town, Nellore. He likes to do farming or yoga when he is not in front of his laptop exploring emerging technologies.

See other products by Avinash Venkateswarlu

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