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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

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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

Chapter 6. The ML Kit SDK

In this chapter, we will discuss ML Kit, which was announced by Firebase at the Google I/O 2018. This SDK packages Google's mobile machine learning offerings under a single umbrella.

Mobile application developers may want to implement features in their mobile apps that require machine learning capabilities. However, they may not have knowledge of machine learning concepts and which algorithms to use for which scenarios, how to build the model, train the model, and so on.

ML Kit tries to address this problem by identifying all the potential use cases for machine learning in the context of mobile devices, and providing ready-made APIs. If the correct inputs are passed to these, the required output is received, with no further coding required.

Additionally, this kit enables the inputs to be passed either to on-device APIs that work offline, or to online APIs that are hosted in the cloud.

To top it all, ML Kit also provides options for developers with expertise in machine...

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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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