Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management

I got this book for a class on Data-Mining and I found it to be a very good book. It has good visuals to help the reader understand the concepts in the book and maintains a good sense of humor throughout so reading it doesn't seem as dense as some of my typical statistics books. My only criticism of the book would be that it never discusses common software platforms for performing these tasks. While I understand that he probably didn't want to favor a particular platform over another, it seems that introducing the major ones could be helpful for people that may be very used to using just one.

I listened to the audio book (35 hrs) and know I’ll want to go over it again. It covered like every topic in data science. Not light reading, but a great book.

In a field evolving as dynamically as data science, 2011 seems a long time ago, and I've since bought a number of the newer titles out there. Still, however, I often find myself reverting to Linoff and Barry's text for a lucid explanation of, or interesting take on a particular data mining subject area.The book is thorough (at 800+ pages this should be the expectation) and technical, but isn't really a how-to manual in that it stops short of containing actual code or instructions. That's not an issue, however, as such instructional information is available elsewhere if needed.My only complaint about the work is that it is a little redundant and otherwise verbose at times. I hope a fourth edition is forthcoming, and that it is a little more tightly edited.---Z. KhandwalaInstitute for Advanced AnalyticsBellarmine University - Louisville, KY

I taught myself data mining using this book. I also was in my MBA Decision Science class the next year and they used the exact same book, but I had already read the book front to back. I aced that class. The book is comprehensive and allows people to grasp all the basic concepts of data mining.

I have read a couple of books about data science. Reading this one is most enjoyable. I cannot put it down. I found a lot of useful information from examples in different industries. Highly recommend. I do have years of hands on experience on data mining.

This book - has a lot of content - all with quite good relevant examples.Where this book fails is - in its technical details. This is probably a good book for managers - who need to know the basics of what this whole thing is about.This book failed to impress me - since I am a technical person - and would like to know the technical and details about the techniques discussed - of when which technique is to be applied and why and - also how the technique works.The coverage of the book is very good - it has a lot of material to read - but at the end of it - I felt still sort of void - that I did not sink in too much - of why and how we are doing all these techniques and how it gives the answers to the relevant questions.

I was looking for a reference book that could bring me a clear picture of all data mining techniques for marketing and CRM, and there it was. But it goes beyond that, it brings many examples and tips that makes the life eaiser to the data miner. Highly recommended.

Fantastic information. I would give five stars if they included some example coding in any of the major languages, SAS, python, R...

Damaged corners and cover.

This book is one of the best in terms of content. The authors take a clear approach starting from business problem definition to questions while designing an analytical solution to possible methods to explore those solutions. Most of the mainstream Data Mining methods, supervised and unsupervised and semi-supervised, are covered along with the underlying concepts and theories. There's is wonderful chapter on application network & graph analyses which can be extended to web analytics. Bonus chapters include basics of text analytics and data structures + warehousing. All examples are contextualised in the marketing domain. But beware: it's not the easiest book to digest if you don't have a good enough technical background.The only small downside is this book was written several years ago, and in terms of tools, feels a bit dated.

Lo libro es muy bueno e de fácil comprensión. Pero lo envío no es el mejor. La frente tenía algún daño.

Das buch ist gut, keine Frage. Als Einsteiger findet man hier alles was man braucht um sich ins Thema und ins gesamte Feld einzuarbeiten. Grundlegende Konzepte zum Data Mining werden aufschlussreich dargelegt und verständlich erklärt. Sobald man jedoch ein wenig tiefer gräbt, wird man spätestens im Abschnitt statistischen Methoden schnell an die Grenzen des Buchs stoßen.Empfehlung: eBook kaufen: Das Buch ist nicht nur inhaltlich schwere Kost. Es bringt einiges an Gewicht auf die Waage, lässt sich nur schwer aufklappen und hinlegen ohne dass man es beschweren muss. Um damit im Alltag zu arbeiten ist es eigentlich zu unhandlich.Daher: Gut - Sehr gut für Einsteiger (je nach Vorwissen im gesamten Themenfeld), befriedigend für Fortgeschrittene.

電話帳のように分厚いですが、それだけの読み応えがあります。今で言うデータサイエンスの基本的な技術（ただし、ディープラーニングやベイジアン・ネットワークなどがないところが、データマイニングの時代を反映しています）について、数式を使わずに、しかも要点は外さずに解説していると言う点がまず第一の特徴です。また、著者らがデータマイニングによる実践的な問題解決の実務に長く携わって来ているので、その経験から、実際にデータをビジネスに活用する際に気をつけなればいけないことが、時には失敗談も含めて詳しく語られています。さらに、データ科学の古典的な話にも触れてあって、どうしてこう言う技術が発達したのかと言う広く・長い視点を得ることができます。こうした視点は複雑多様なデータサイエンスの各手法を自分なりに位置付けるのにとても有効です。英語は平易（ただし、出版社の問題でtypoが散見されます）ですので、英語のハードルは低いです。翻訳もあります（自分で翻訳分担者でもありますが）が、抄訳で訳していないところにも面白くてためになることがいっぱい書いてありますので、ぜひ、原文で全文にトライしてみてください。その価値はあると思います。大学の合格祝いにプレゼントしたり、これからデータサイエンスを学びたいと言う人に薦めています。