Beginning Artificial Intelligence with the Raspberry Pi

Highly readable introduction to AImost AI books are either graduate level texts or very specific and slated to a niche market.
Gain a good handle of AI using the Raspberry Pi
Create an actual and successful AI project using the Raspberry Pi

Autorentext
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.

Zusammenfassung
Using the Raspberry Pi as the computing platform, this book explores most of the major AI topics, including expert systems, machine learning both shallow and deep, fuzzy logic control and more. A series of projects will walk through how to implement the AI concepts. Minimal expense is needed as only a few sensors and actuators will be required.

Inhalt
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