Book Image

Machine Learning for Mobile

By : Revathi Gopalakrishnan, Avinash Venkateswarlu
Book Image

Machine Learning for Mobile

By: Revathi Gopalakrishnan, Avinash Venkateswarlu

Overview of this book

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. You will begin with an introduction to machine learning on mobiles and grasp the fundamentals so you become well-acquainted with the subject. You will master supervised and unsupervised learning algorithms, and then learn how to build a machine learning model using mobile-based libraries such as Core ML, TensorFlow Lite, ML Kit, and Fritz on Android and iOS platforms. In doing so, you will also tackle some common and not-so-common machine learning problems with regard to Computer Vision and other real-world domains. By the end of this book, you will have explored machine learning in depth and implemented on-device machine learning with ease, thereby gaining a thorough understanding of how to run, create, and build real-time machine-learning applications on your mobile devices.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Question and Answers
Index

Chapter 5. Regression Using Core ML in iOS

This chapter will provide you with an overview of regression algorithms and insights into the basics of Core ML, and will introduce you to creating a machine learning program leveraging a regression algorithm and predicting the housing price for a given set of housing-related data using Core ML in iOS.

As we already saw in Chapter 1Introduction to Machine Learning on Mobile, any machine learning program has four phases. We will see what we are going to cover in the four phases and what tools we are going to use to solve the underlying machine learning problem.

Problem definition: The housing information of a certain area is provided and we want to predict the median value of a home in this area.

We will be covering the following topics in the chapter:

  • Understanding what regression is and how to apply it to solve an ML problem
  • Understanding regression using a sample dataset and Excel
  • Understanding the basics of Core ML
  • Solving the problem using regression...