Raspberry Pi 3 Cookbook for Python Programmers 3E

Unleash the potential of Raspberry Pi 3 with over 100 recipes

Tim Cox , Dr. Steven Lawrence Fernandes 지음

Packt(GCO Science) 2018년 04월 30일 출간

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목차

▶TABLE of CONTENTS
1: GETTING STARTED WITH A RASPBERRY PI 3 COMPUTER
2: DIVIDING TEXT DATA AND BUILDING TEXT CLASSIFIERS
3: USING PYTHON FOR AUTOMATION AND PRODUCTIVITY
4: PREDICTING SENTIMENTS IN WORDS
5: CREATING GAMES AND GRAPHICS
6: DETECTING EDGES AND CONTOURS IN IMAGES
7: CREATING 3D GRAPHICS
8: BUILDING FACE DETECTOR AND FACE RECOGNITION APPLICATIONS
9: USING PYTHON TO DRIVE HARDWARE
10: SENSING AND DISPLAYING REAL-WORLD DATA
11: BUILDING NEURAL NETWORK MODULES FOR OPTICAL CHARACTER RECOGNITION
12: BUILDING ROBOTS
13: INTERFACING WITH TECHNOLOGY
14: CAN I RECOMMEND A MOVIE FOR YOU?

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▶What this book covers
？ Chapter 1, Getting Started with a Raspberry Pi Computer, introduces the Raspberry Pi and explores the various ways in which it can be set up and used.

？ Chapter 2, Dividing Text Data and Building a Text Classifier, guides us to build a text classifier; it can classify text using the bag-of-words model.

？ Chapter 3, Using Python for Automation and Productivity, explains how to use graphical user interfaces to create your own applications and utilities.

？ Chapter 4, Predicting Sentiments in Words, explains how Naive Bayes classifiers and logistic regression classifiers are constructed to analyze the sentiment in words.

？ Chapter 5, Creating Games and Graphics, explains how to create a drawing application and graphical games using the Tkinter canvas.

？ Chapter 6, 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.

？ Chapter 7, Creating 3D Graphics, discusses how we can use the hidden power of the Raspberry Pi's graphical processing unit to learn about 3D graphics and landscapes, and produce our very own 3D maze for exploration.

？ Chapter 8, Building Face Detector and Face Recognition Applications, explains how human faces can be detected from webcams and recognized using images stored in a database.

？ Chapter 9, Using Python to Drive Hardware, establishes the fact that to experience the Raspberry Pi at its best, we really have to use it with our own electronics. This chapter discusses how to create circuits with LEDs and switches, and how to use them to indicate the status of a system and provide control. Finally, it shows us how to create our own game controller, light display, and a persistence-of-vision text display.

？ Chapter 10, Sensing and Displaying Real-World Data, explains how to use an analog-todigital converter to provide sensor readings to the Raspberry Pi. We discover how to store and graph the data in real time, as well as display it on an LCD text display. Next, we record the data in a SQL database and display it in our own web server. Finally, we transfer the data to the internet, which will allow us to view and share the captured data anywhere in the world.

？ Chapter 11, Building a Neural Network Module for Optical Character Recognition, introduces neural network implementation on Raspberry Pi 3. Optical characters are detected, displayed, and recognized using neural networks.

？ Chapter 12, Building Robots, takes you through building two different types of robot (a Rover-Pi and a Pi-Bug), plus driving a servo-based robot arm. We look at motor and servo control methods, using sensors, and adding a compass sensor for navigation.

？ Chapter 13, Interfacing with Technology, teaches us how to use the Raspberry Pi to trigger remote mains sockets, with which we can control household appliances. We learn how to communicate with the Raspberry Pi over a serial interface and use a smartphone to control everything using Bluetooth. Finally, we look at creating our own applications to control USB devices.

？ Chapter 14, Can I Recommend a Movie for You?, explains how movie recommender systems are built. It elaborates how Euclidean distance and Pearson correlation scores are computed. It also explains how similar users are found in the dataset and the movie recommender module is built.

？ Appendix, Hardware and Software List, explains the detailed hardware software list used inside the book.

출판사 서평

▶Editorial Review
This book is intended for anyone who wants to build software applications or hardware projects using the Raspberry Pi. The book gradually introduces text classification, creating games, 3D graphics, and sentiment analysis. We also move towards more advanced topics, such as building computer vision applications, robots, and neural network applications. It would be ideal to have basic understanding of Python; however, all programming concepts are explained in detail. All the examples are written using Python 3, with clear and detailed explanations of how everything works so that you can adapt and use all the information in your own projects. By the end of the book, you will have the skills you need to build innovative software applications and hardware projects using the Raspberry Pi.

작가정보

저자(글) Tim Cox

Tim Cox lives in England with his wife and two young daughters and works as a software engineer. His passion for programming stems from a Sinclair Spectrum that sparked his interest in computers and electronics. At university, he earned a BEng in Electronics and Electrical Engineering, and into a career in developing embedded software for a range of industries.Supporting the vision behind the Raspberry Pi, to encourage a new generation of engineers, Tim co-founded the MagPi magazine (the official magazine for the Raspberry Pi) and produces electronic kits through his site PiHardware.

저자(글) Dr. Steven Lawrence Fernandes

Dr. Steven Lawrence Fernandes has Postdoctoral Research experience working in the area of Deep Learning at The University of Alabama at Birmingham, USA. He has received the prestigious US award from 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 Research Grant from The Institution of Engineers.He has completed his B.E (Electronics and Communication Engineering) and M.Tech (Microelectronics) and Ph.D. (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).