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Machine Learning for Mobile, published by Packt

License: MIT License

Jupyter Notebook 0.23% CMake 0.05% Java 1.23% C++ 92.30% C 3.98% Objective-C 0.05% Python 1.74% Swift 0.40% Ruby 0.01%

machine-learning-for-mobile's Introduction

Machine Learning for Mobile

Machine Learning for Mobile

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

Practical guide to building intelligent mobile applications powered by machine learning

What is this book about?

Machine learning presents an entirely unique opportunity in software development. It allows smartphones to produce an enormous amount of useful data that can be mined, analyzed, and used to make predictions. This book will help you master machine learning for mobile devices with easy-to-follow, practical examples.

This book covers the following exciting features: <First 5 What you'll learn points>

  • Build intelligent machine learning models that run on Android and iOS
  • Use machine learning toolkits such as Core ML, TensorFlow Lite, and more
  • Learn how to use Google Mobile Vision in your mobile apps
  • Build a spam message detection system using Linear SVM
  • Using Core ML to implement a regression model for iOS devices

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:

# importing required packages
import numpy as np
import pandas as pd

Following is what you need for this book:

If you are a mobile app developer or a machine learning enthusiast keen to use machine learning to build smart mobile applications, this book is for you. Some experience with mobile application development is all you need to get started with this book. Prior experience with machine learning will be an added bonus

With the following software and hardware list you can run all code files present in the book (Chapter 1-15).

Software and Hardware List

Chapter Software required OS required
4, 5, 6, 8, 10 Xcode Mac OS X
3, 4, 5, 6, 7, 8,10 PyCharm, Python Mac OS X
3, 5, 7, 9 Android Studio Mac OS X

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

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Get to Know the Authors

Revathi Gopalakrishnan is a software professional with more than 17 years of experience in the IT industry. She has worked extensively in mobile application development and has played various roles, including developer and architect, and has led various enterprise mobile enablement initiatives for large organizations. She has also worked on a host of consumer applications for various customers around the globe. She has an interest in emerging areas, and machine learning is one of them. Through this book, she has tried to bring out how machine learning can make mobile application development more interesting and super cool. Revathi resides in Chennai and enjoys her weekends with her husband and her two lovely daughters.

Avinash Venkateswarlu has more than 3 years' experience in IT and is currently exploring mobile machine learning. He has worked in enterprise mobile enablement projects and is interested in emerging technologies such as mobile machine learning and cryptocurrency. Venkateswarlu works in Chennai, but enjoys spending his weekends in his home town, Nellore. He likes to do farming or yoga when he is not in front of his laptop exploring emerging technologies.

Suggestions and Feedback

Click here if you have any feedback or suggestions.

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781788629355

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