Current Reading in Data Mining

February 7, 2010 by
Filed under: Uncategorized 

I’m currently reading two interesting books about analytics and data mining. I will review these two books in the near future. Meanwhile, here is a few information about these books:

  • Analytics at Work (Davenport/Harris): I recently had the chance to receive an advance reader’s copy of this book (publication date: February 12th). Comparing to Competing on Analytics, Analytics at Work is for a larger audience since it explains how any company can improve in analytics. This book is easy to read and contains a lot of advices for anybody involved in this field.
  • Handbook of Statistical Analysis and Data Mining Applications (Nisbet/Elder/Miner): I heard a lot about this book. It seems to be THE new book about data mining. So I wanted to check by myself. I have to admit that it is a very interesting reading but since it is not theoretical, it is more beginner oriented. However, the applications and examples in SAS, Clementine and STATISTICA are very well presented. It is a new and fresh approach to data mining, which is very pleasant to read.

Even before making the final reviews, I can already recommend you these two books. Happy reading!

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3 Comments on Current Reading in Data Mining

  1. Adnan on Sun, 14th Feb 2010 10:29 am
  2. I am interested to learn more about Collective Intelligence which is based on Text Mining and other things. Can you guide me where should I start from? I am basically a web developer

  3. Darckeen on Thu, 4th Mar 2010 7:07 pm
  4. Hey, great blog. I found your site via your review of Introduction to Data Mining on amazon. I think i’ll pick that up for my next book. I’m currious, in your review you said that it wasn’t a good book for learning about kernels. Do you have a suggestion for a introductory book on kernel methods?

  5. Sandro Saitta on Thu, 4th Mar 2010 9:52 pm
  6. @Darckeen: Happy that you liked the blog! For kernel book I would suggest this one: http://www.dataminingblog.com/small-book-review-an-introduction-to-support-vector-machines-and-other-kernel-based-learning-methods/ But as I write it is quite technical. Any good data mining book will have a chapter on SVM or kernel methods in general.

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