Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more!
AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations.
A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book.
What You'll Learn
- What AI is and-as importantly-what it is not
- Inference and expert systems
- Machine learning both shallow and deep
- Fuzzy logic and how to apply to an actual control system
- When AI might be appropriate to include in a system
- Constraints and limitations of the Raspberry Pi AI implementation
Who This Book Is For
Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.
Rezensionen / Stimmen
"This book is a practical introduction to the field of artificial intelligence (AI) that can serve as either a primer to the subject or a companion to theoretical studies. . Summing Up: Recommended. Lower- and upper-division undergraduates; professionals and practitioners." (J. M. Smith, Choice, Vol. 55 (6), February, 2018)
Auflage
Sprache
Verlagsort
Zielgruppe
Illustrationen
64
122 farbige Abbildungen, 64 s/w Abbildungen
XXI, 369 p. 186 illus., 122 illus. in color.
Maße
Höhe: 235 mm
Breite: 155 mm
Dicke: 22 mm
Gewicht
ISBN-13
978-1-4842-2742-8 (9781484227428)
DOI
10.1007/978-1-4842-2743-5
Schweitzer Klassifikation
Donald J. Norris has a degree in electrical engineering and an MBA specializing in production management. He teaches undergrad and grad courses in the IT subject area at Southern New Hampshire University. He also created and teaches several robotics courses there. He has over 36 years of teaching experience as an adjunct professor at a variety of colleges and universities. Mr. Norris retired from civilian government service with the U.S. Navy, where he specialized in acoustics related to nuclear submarines and associated advanced digital signal processing. Since then, he has spent more than 22 years as a professional software developer using C, C#, C++, Python, Node.js and Java, as well as 5 years as a certified IT security consultant. Mr. Norris started a consultancy, Norris Embedded Software Solutions (dba NESS LLC), that specializes in developing application solutions using microprocessors and microcontrollers. He likes to think of himself as a perpetual hobbyist and geek and is always trying out new approaches and out-of-the-box experiments. He is a licensed private pilot, photography buff, amateur radio operator, and avid runner.
Chapter 1: Introduction to Artificial Intelligence (AI).- Chapter 2: Basic AI Concepts.- Chapter 3: Expert System Demonstrations.- Chapter 4: Games.- Chapter 5: Fuzzy Logic Systems.- Chapter 6: Machine Learning.- Chapter 7: Machine Learning - Artificial Neural Networks.- Chapter 8: Machine Learning - Deep Learning.- Chapter 9: Machine learning - Practical ANN Demonstration .- Chapter 10: Evolutionary Computing.- Chapter 11: Behavior-Based Robotics.- Appendix A: Build Instructions for the Alfie Robot Car
