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Prof. Diwakar Vaish - Getting Started with Python for the Internet of Things

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Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python.

Key Features
  • Create your own Pi-Rover or Pi-Hexipod robots
  • Develop practical applications in Python using Raspberry Pi
  • Build your own Jarvis, a highly advanced computerized AI
Book Description

This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python.

It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, youll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment.

By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python.

  • Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes
  • Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor
  • Python Robotics Projects by Prof. Diwakar Vaish
What you will learn
  • Build text classifiers and predict sentiment in words with the Tkinter library
  • Develop human face detection and recognition systems
  • Create a neural network module for optical character recognition
  • Build a mobile robot using the Raspberry Pi as a controller
  • Understand how to interface sensors, actuators, and LED displays work
  • Apply machine learning techniques to your models
  • Interface your robots with Bluetooth
Who this book is for

This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance peoples lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.

Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.

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Getting Started with Python for the Internet of Things Leverage the full - photo 1
Getting Started with Python for the Internet of Things
Leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi
Tim Cox
Dr. Steven Lawrence Fernandes
Sai Yamanoor
Srihari Yamanoor
Prof. Diwakar Vaish

BIRMINGHAM - MUMBAI Getting Started with Python for the Internet of Things - photo 2

BIRMINGHAM - MUMBAI
Getting Started with Python for the Internet of Things

Copyright 2019 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors nor Packt Publishing or its dealers and distributors will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavoured to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: February 2019

Production reference: 1250219

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-83855-579-5

www.packtpub.com

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Contributors
About the authors

Tim Cox works as a software engineer and is passionate about programming. He holds a bachelor's degree in electronics and electrical engineering and has a rich career in developing embedded software for a range of industries. To support the vision behind the Raspberry Pi and to encourage a new generation of engineers, Tim co-founded the MagPi magazine (the official magazine for the Raspberry Pi). He also produces electronic kits through his site PiHardware.

Dr. Steven Lawrence Fernandes holds a bachelor's degree in electronics and communication engineering, a master's degree in microelectronics, and a Ph.D. in computer vision and machine learning. His Ph.D work "Match composite sketch with drone images" has received patent notification (Patent Application Number: 2983/CHE/2015). has post the doctoral research experience working in deep learning at the University of Alabama at Birmingham, USA. He received the prestigious US award from the Society for Design and Process Science for his outstanding service contributions in 2017 and Young Scientist Award by Vision Group on Science and Technology in 2014. He has also received a research grant from the Institution of Engineers.

Sai Yamanoor is an embedded systems engineer working for a private startup school in the San Francisco Bay Area, where he builds devices that help students achieve their full potential. He completed his undergraduate work in mechatronics engineering from Sri Krishna College of Engineering and Technology, Coimbatore, India and his graduate studies in mechanical engineering at Carnegie Mellon University, Pittsburgh PA. His interests, deeply rooted in DIY and open software and hardware cultures, include developing gadgets and apps that improve the quality of life, Internet of Things, crowdfunding, education, and new technologies. In his spare time, he plays with various devices and architectures, such as the Raspberry Pi, Arduino, Galileo, Android devices and others. Sai has earlier published a book titled Raspberry Pi Mechatronics Projects.

Srihari Yamanoor is a mechanical engineer, working on medical devices, sustainability, and robotics in the San Francisco Bay Area. He completed his undergraduate studies in mechanical engineering from PSG College of Technology, Coimbatore, India and graduate studies in mechanical engineering at Stanford University. He is certified in SolidWorks, simulation, sustainable design, PDM as well as in quality and reliability engineering and auditing. His has a wide range of interests, from DIY, crowdfunding, AI, travelling, photography to gardening and ecology.

Prof. Diwakar Vaish is a robotics scientist and the inventor of Manav, India's first indigenous humanoid robot. He has invented the world's first mind-controlled wheelchair, brain cloning, and the world's cheapest ventilator. He has also been a guest lecturer at over 13 IITs and various other institutions. He is the founder of A-SET Robotics, a leading robotics research company based in New Delhi.

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What this book covers

, Getting Started with a Raspberry Pi 3 Computer, introduces the Raspberry Pi and explores the various ways in which it can be set up and used.

, Dividing Text Data and Building Text Classifiers, guides us to build a text classifier; it can classify text using the bag-of-words model.

, Using Python for Automation and Productivity, explains how to use graphical user interfaces to create your own applications and utilities.

, Predicting Sentiments in Words, explains how Naive Bayes classifiers and logistic regression classifiers are constructed to analyze the sentiment in words

, Detecting Edges and Contours in Images, describes in detail how images are loaded, displayed, and saved. It provides detailed implementations of erosion and dilation, image segmentation, histogram equalization, edge detection, detecting corners in images, and more.

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