This book is excellent since it is mathematical and detailed. It covers some advanced topics which will not be covered in this course. This book cover most of the material of the course, but is very descriptive and lacking in detail. Coverage of validation is excellent. A collection of current applications of the techniques from this course.
Some introductory material is included.
The classic work on traditional methods of pattern classification. This book would be useful on Bayesian classification, neural networks, and some of the search aspects of the course but contains nothing on validation or non-numerical methods. Thornton, C. J., techniques in Computational Learning. Further Supplementary Reading These two books put neural networks in a modern statistical context. Symbolic versus subsymbolic methods, hand-built knowledge versus model extraction from data.