Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) 3rd Edition

Needless to say, this is a classic book for data mining.It presents an extraordinary clear flow of materials. The essences of the difficult and challenging research publications are extractedand transformed into a domain even novice could catch the points.For practitioner who wish to get quick and broad-based overview, this book is for you.For students who are going to do research in this area, this is probably the place you should embark

The books is very well written and explains the concepts in a very simple manner. It covers all the algorithms with good examples. A must for a person who wants to learn the concepts of data mining.

Overall a decent book for begininers like myself.Pros:- Historical laydown- In depth discussion on subject matter- Plenty of examples and problems to work throughCons:- In the examples it kinda jumps from SQL to others. Wish the author would have picked something and rolled with it. I understand the benefits of discussion multiple options, but that's just my personal preference.- A little dry and hard to read for a long period of time. I had to take breaks every 10-20 min and look at something else.

The book is in an excellent state 👌

This is a great book for who is starting at data mining.It gives us a solid concept definition about data mining concepts, and common techniques.If you are willing to buy a theoretical book about data mining, this is the one.

This is a robust and practical book explaining concept of data mining. I bought this as a textbook for Data Mining class at a grad school. Some chapters require quantitative background but in general it is relatively easy to read.

If you suffer from insomnia then this book is just the thing for you. If, however, you are new to data mining and do not already have a statistical background then this book is absolutely awful. The writing is overly repetitive, as if the authors wrote separately and didn't compare what they had written before just merging it all together, and there aren't nearly enough visuals. The concepts and formulas could be explained so much more simply if the authors would just use plain speech instead of relying upon their "pseudo code."

I'm using this book for a Data Mining class in grad. school. I'd never taken a data mining course. Considering that it was a brand new topic to me, I'd say that I've come a long. Granted, I have a great professor, but the textbook deserves a lot of credit too. It explains all of the steps in the Knowledge Discovery/Data Mining process and some key techniques in a way that left me feeling confident and wanting to learn more.The author(s) did a great job of explaining complex topics. It's a textbook, so there's a good combination of both theory and math. I like the way that the book uses one company as the focus of examples for the entire book. It's creates continuity. I will admit that there are a few points where the author assumes that the reader knows a math concept and doesn't explain it, but overall, if you have at least an introductory level knowledge of statistics, you'll be fine. .