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

The book is in an excellent state 👌

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

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. .

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.

Great Book. Easy to read

The book was in a better condition than advertised, and it arrived just before it was supposed to.

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."

The content of the book seems pretty good. I have only got up to about chapter four so far and it's easy to read and introduces material in a reasonably gentle manner. The three stars are due to the fact that I am using the electronic version, on a kindle app on an Android tablet, and it has some issues. It is mostly OK but suffers because quite a lot of the technical material is scanned rather than true font or vector which means that if you zoom in, the surrounding text gets bigger but the figures, formula and diagrams often don't. This is particularly troublesome for mathematical formulas which are sometimes scanned at quiet low resolution and very difficult to decipher, not great when they are already quite complex to understand.It's usable though, much more convenient in electronic form and I've saved myself about $50 by renting the book on Amazon for four months compared to buying it at the Uni bookshop.

Fine package and book in good conditions 👍

Le livre était exactement tel que décrit dans la description (couverture légèrement endommagée, mais intérieur intact). Livraison Prime qui ne respectait pas le 2 jours, mais qui a été assez efficace tout de même.

Come da titolo, è un buon libro. Fornisce una panoramica delle tecniche ( avanzate e basilari) di data minino. Molti capitoli sono spiegati davvero bene, altri un po' meno. Il problema è che un libro che lascia un po' l'amaro in bocca. In alcuni capitoli ti spiega molto da un punto di vista teorico, poco in quello pratico. Non per nulla l'ho usato come libro di supporto al famoso "mining of massive datasets"( anche se, ad esempio, a differenza di quest'ultimo, la parte di machine Learning ovvero SVM è molto più chiara qui). Inoltre, contiene spiegazioni di algoritmi che non ho visto in altri libri, quindi rimane un libro secondario da usare insieme ad altri testi.

This is a great book if you are looking for a concept-driven textbook and strong overview of data mining. I find myself reaching for this book more than my more traditionally academic books when working with others. The people I work with want to understand how the techniques work in general; they aren't after impressive equations or technical language, impressive though it might sound. The more conversational tone is accessible and ease to dip back into for a reminder when used as a high level reference text.Overall, an especially good library addition for people working with non-stats people.

It approaches the topics in a very easy way, I'm new on the topic, with a university background, not specially good a statistics, but this book is being easy to read & understand.