Excellent Introduction

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This is one of the best introductions into statistical pattern recognition that you will find. Explains the mathematics behind the algorithms very effectively. Used this text in a grad course a couple years ago but you don't need to be a grad student to understand and use the concepts in this text, I have re-read various chapters of this books while working and its a great asset. Note that although it has great coverage of the math used in pattern recognition it won't review the math, you should know it. If you don't have a good grasp of calculus and linear algebra then you probably should go back and learn the math before reading this book, and to be blunt you really shouldn't be getting into pattern recognition if you don't know the math anyway. I would have given 5 stars if they had code written in an actual language rather than pseudo code (with bad variable names). I still don't get why authors don't pick a descriptive language that any programmer can understand like Python or R to show you examples rather than pseudo code. But overall, you'll be happy with this purchase

Weak notation but simplified ideas

This book is okay. It prevents some AI ideas in a simplified contexts. When resorting to mathematics, its notation is quite weak and can lead to confusion.

Its short, it prevents some intuitions that are nice but all in all, Duda, Heart and Storkes book is still far better.