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

Introduction to neural networks


A neural network is a system of hardware and/or software that is modeled on the operation of neurons in the human brain. The design behind neural networks is inspired by the human brain and its functionality. Let's understand the design of the human brain. The neuron is the basic working unit of the brain. It's a specialized cell that can transmit information to other nerve cells. The brain is made up of approximately 100,000,000,000 neurons. A neuron's main function is to process and transmit information.

Communication steps of  a neuron

Neuron communication follows a four-step path:

  • A neuron receives information from the external environment or from other neurons.
  • The neuron integrates, or processes, the information from all of its input and determines whether to send an output signal. This integration takes place both in time (the duration of the input and the time between input) and space (across the surface of the neuron).
  • The neuron propagates the signal...