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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

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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