I decided to start with this book as I think it is the most convenient to start in the data mining field. One big advantage of the book is the way data mining techniques are explained. It is mainly based on textual and graphical explanations. There is little equations, only what is necessary to implement the algorithms.
This book widely cover areas such as data preparation and understanding, classification, anomaly detection, association analysis and clustering. Although the book has a strong emphasis on the two last ones, nearly all standard data mining techniques are at least briefly discussed. However, this book does only have a fiew pages about kernel methods for example. Indeed, it is normal, as kernel methods are more suitable for machine learning (I mean making prediction) than data mining (I mean looking for description).
Therefore, this book is:
- able to explain data mining without thousands of equations
- a good way to start with data mining
- covering nearly all standard data mining techniques
- focused on association analysis and clustering
and it is not:
- a good book for kernel methods and other advanced techniques
- written in the statistical nor in the database perspective
My comment: if you are in the data mining field and not coming from mathematics or databases, then you really should buy this book. I finally remember you that this comments only imply me.