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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

Sample mobile application using Google Cloud Vision

In this section, we are going to try a sample Android mobile application using Google Cloud Vision. We are going to capture an image from the camera of the cell phone, upload the image to Google Cloud Vision, and see what it predicts the image to be. This is going to use the label detection feature of Google Cloud Vision, which determines the label of the uploaded image.

How does label detection work?

The Vision API can detect and extract information about entities within an image, across a broad group of categories. Labels can identify objects, locations, activities, animal species, products, and more. Labels are returned in English only.

The image whose label is to be determined and the features of the Google Vision that we intend to use needs to be sent in the request API. The feature can be any of the features listed in the Features of Google Cloud Vision section, such as label detection or logo detection. If there is any additional image...

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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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