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Machine Learning Projects for Mobile Applications

You're reading from Machine Learning Projects for Mobile Applications

Product type Book

Published in Oct 2018

Publisher Packt

ISBN-13 9781788994590

Pages 246 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Karthikeyan NG

Table of Contents (16) Chapters

Title Page

Dedication

Packt Upsell

Contributors

Preface

1. Mobile Landscapes in Machine Learning

2. CNN Based Age and Gender Identification Using Core ML

3. Applying Neural Style Transfer on Photos

4. Deep Diving into the ML Kit with Firebase

5. A Snapchat-Like AR Filter on Android

6. Handwritten Digit Classifier Using Adversarial Learning

7. Face-Swapping with Your Friends Using OpenCV

8. Classifying Food Using Transfer Learning

9. What's Next?

1. Other Books You May Enjoy

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Index

Summary

In this chapter, we learned to build a style transfer app from an art form. Now, we are very much familiar with how deep CNNs work and how layers process data. We have also become familiar with building the basic foundations of an iOS app and an Android app.

In the next chapter, we will discuss applying machine learning using Firebase's ML Kit framework in more detail.

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Authors (1)

Karthikeyan NG

Karthikeyan NG is the Head of Engineering and Technology at the Indian lifestyle and fashion retail brand. He served as a software engineer at Symantec Corporation and has worked with 2 US-based startups as an early employee and has built various products. He has 9+ years of experience in various scalable products using Web, Mobile, ML, AR, and VR technologies. He is an aspiring entrepreneur and technology evangelist. His interests lie in exploring new technologies and innovative ideas to resolve a problem. He has also bagged prizes from more than 15 hackathons, is a TEDx speaker and a speaker at technology conferences and meetups as well as guest lecturer at a Bengaluru University. When not at work, he is found trekking.

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