Artificial Intelligence for Humans, Volume 1: Fundamental Algorithms
| Author | : | |
| Rating | : | 4.58 (841 Votes) |
| Asin | : | 1493682229 |
| Format Type | : | paperback |
| Number of Pages | : | 222 Pages |
| Publish Date | : | 2016-01-25 |
| Language | : | English |
DESCRIPTION:
His areas of expertise include Data Science, Predictive Modeling, Data Mining, Big Data, Business Intelligence, and Artificial Intelligence. Jeff holds a Master’s Degree in Information Management from Washington University and is a Senior Member of the IEEE, a Sun Certified Java Programmer, the lead developer for the Encog Machine Learning Framework open source project, and an Associate of Reinsurance Administration (ARA, LOMA). About the Author Jeff Heaton is an Informatics Scientist programmer specializing in Java, C#, Groovy, Scala, C/C++, SQL, R, and Octave. . He is an active techno
The reader needs only a knowledge of basic college algebra or computer programming—anything more complicated than that is thoroughly explained. Every chapter also includes a programming example. A great building requires a strong foundation. Artificial Intelligence for Humans is a book series meant to teach AI to those without an extensive mathematical background. This book teaches basic Artificial Intelligence algorithms such as dimensionality, distance metrics, clustering, error calculation, hill climbing, Nelder Mead, and linear regression. These are not just foundational algorithms for the rest of the series, but are very useful in their own right. The book explains all algorithms using actual numeric calculations that you can perform yourself. Examples are currently provided in Java, C#, R, Python and C. Other languages planned.
Michael R. Morrison said Five Stars. received on time and is as advertised.. Four Stars Hoped more!. A good primer for AI Brookemeister I've wanted to better understand artificial intelligence for a long time. This book has opened the door for me. It requires a little mathematical aptitude, but little else, as the author starts with basic concepts and gradually builds on them. I like the examples and illustrations. They helped me digest and build my understanding one step at a time.I've been in contact with the author and found out that, with self-publishing, you can pretty immediately turn around reader feedback and make incremental improvements to the book. Since I bought the book last month, a number of improvements hav
. Jeff Heaton is an Informatics Scientist programmer specializing in Java, C#, Groovy, Scala, C/C++, SQL, R, and Octave. His areas of expertise include Data Science, Predictive Modeling, Data Mining, Big Data, Business Intelligence, and Artificial Intelligence. He is an active technology blogger, open source contributor, and author of more than ten books. Jeff holds a Ma