/Machine-Learning-Projects-for-Mobile-Applications

Machine Learning Projects for Mobile Applications, published by Packt

Primary LanguageJavaMIT LicenseMIT

Machine Learning Projects for Mobile Applications

Machine Learning Projects for Mobile Applications

This is the code repository for Machine Learning Projects for Mobile Applications, published by Packt.

Build Android and iOS applications using TensorFlow Lite and Core ML

What is this book about?

Machine learning is a technique that focuses on developing computer programs that can be modified when exposed to new data. We can make use of it for our mobile applications and this book will show you how to do so.

This book covers the following exciting features:

  • Demystify the machine learning landscape on mobile
  • Age and gender detection using TensorFlow Lite and Core ML
  • Use ML Kit for Firebase for in-text detection, face detection, and barcode scanning
  • Create a digit classifier using adversarial learning
  • Build a cross-platform application with face filters using OpenCV

If you feel this book is for you, get your copy today!

https://www.packtpub.com/

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

def estimate_house_price(sqft, location):
price = < DO MAGIC HERE >
return price

Following is what you need for this book: Machine Learning Projects for Mobile Applications is for you if you are a data scientist, machine learning expert, deep learning, or AI enthusiast who fancies mastering machine learning and deep learning implementation with practical examples using TensorFlow Lite and CoreML. Basic knowledge of Python programming language would be an added advantage.

With the following software and hardware list you can run all code files present in the book (Chapter 1-8).

Software and Hardware List

Chapter Software required OS required
1 -8 Tensorflow Ubuntu 16.04 or later Windows 7 or later
macOS 10.12.6 (Sierra) or later (no GPU support)
Raspbian 9.0 or later
Android Studio Microsoft Windows 7/8/10 (32-bit or 64-bit),
64-bit required for native debugging
Mac OS X 10.10 (Yosemite) or higher, up to 10.13
(macOS High Sierra) GNOME or KDE desktop
Linux (64 bit capable of running 32-bit applications)
(GNU C Library (glibc)2.19+)
Xcode macOS High Sierra

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. [https://www.packtpub.com/sites/default/files/downloads/9781788994590_ColorImages.pdf].

Code in Action

Click on the following link to see the Code in Action:

Placeholder link

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Get to Know the Author

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 two 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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