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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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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

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Imagine you go to a restaurant with your friends. Assume you are a fitness freak and though you have come to the party to enjoy the buffet, as a fitness freak, you are calorie conscious and don't want to go overboard.

Now, imagine you have a mobile application that comes to your rescue: it takes a picture of the dish, identifies its ingredients, and calculates the caloric value of the food! You could take a picture of every dish and calculate its caloric value and can then decide whether to put it on your plate. Further, this app keeps on learning the different dishes that you take pictures of and continues to learn and master itself in this trade so that it can take very good care of your health.

I can see the sparkle in your eyes. Yes, this is the mobile application we want to try in this chapter. We also want to utilize both TensorFlow and Core ML to accomplish this activity. We will be performing the following steps to create the application that we just discussed...

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