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Machine Learning Projects for Mobile Applications

You're reading from   Machine Learning Projects for Mobile Applications Build Android and iOS applications using TensorFlow Lite and Core ML

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788994590
Length 246 pages
Edition 1st Edition
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Author (1):
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Karthikeyan NG Karthikeyan NG
Author Profile Icon Karthikeyan NG
Karthikeyan NG
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What you have learned so far


In this book, we have covered seven mobile applications, using everyday, real-time use cases. In Chapter 1, Mobile Landscapes in Machine Learning, we covered the basics of ML-based applications, as well as the basics of building a model yourself. In Chapter 2, CNN Based Age and Gender Identification Using Core ML, you learned how to predict the age and gender of a person from an image or camera by using Core ML. In Chapter 3, Applying Neural Style Transfer on Photos, we applied a neural artistic-style transfer algorithm that is widely in use by image editing applications. This was done in the same way for both Android and iOS applications.

In Chapter 4, Deep Diving into the ML Kit with Firebase, we explored how to use the Firebase mobile SDK for face recognition, text prediction, and landmark prediction. If you are a beginner, you can start by utilizing the SDK on either Android or the iOS platform, without worrying about how to develop the model or how to generate...

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