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Book Data Mining with Microsoft SQL Server 2008 by Jamie MacLennan (2008-11-17)

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Data Mining with Microsoft SQL Server 2008 by Jamie MacLennan (2008-11-17)

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    Available in PDF - DJVU Format | Data Mining with Microsoft SQL Server 2008 by Jamie MacLennan (2008-11-17).pdf | Language: UNKNOWN
    Jamie MacLennan;ZhaoHui Tang;Bogdan Crivat(Author)

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3.4 (6072)
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Read online or download a free book: Data Mining with Microsoft SQL Server 2008 by Jamie MacLennan (2008-11-17)

 

Review Text

  • By SergioN on April 9, 2013

    A very well balanced writing with the correct proportion between theory and practise. This was what I was looking for.

  • By DR GREGORY N LOW on May 15, 2011

    This is a superb book. I was sad to see when Jamie moved on from Microsoft (well sad for the product team at least, perhaps not for him as his new venture looks exciting). But this book is a must-read for anyone starting to get involved with Data Mining in SQL Server 2008.

  • By Guille on March 30, 2013

    Nice to start with data mining and Microsoft SQL server, but is necessary to know another tools too, like sas and spss.

  • By Patricia Carter on December 5, 2009

    This is an excellent book for beginner to expert. Contains tons of relevant information. Could have been more detailed for the beginner, but authors did as well as possible without having to write a multi-volume version. Mid level to expert users should have no problem understanding the examples and solutions used in the book. I strongly recommend this book.

  • By Amazon Buyer on April 4, 2014

    I got this used book from thrift_books. Book looks great for the price. Well maintained and they took 4 days to ship it. I just started reading this book. I directly jumped to the Mining with Cubes ( had basic idea about mining) and the example are easy to understand and implement.

  • By Dimitri Shvorob on June 18, 2015

    Sorry, this is not a five-star product. I am on page 104, and already- The brief descriptions of data-mining tasks on pp. 6-10 are wobbly.- Chapter 2's choice to delve into DMX syntax before a single walk-through exercise has been presented is unfortunate. It would have been so much better to introduce those operators and functions *in* the exercises, and maybe summarize in the end. One can easily fall asleep somewhere between p. 60 and p. 75.- The database to be used for the exercise in Chapter 3 is found in the "Chapter 4" folder of the downloadable archive. The "Chapter 3" folder contains a completely different database.- The writing just isn't good. Take pp. 104-105: the authors are meant to be walking through an exercise, but go off on a two-page tangent, leaving uncommented screenshots to guide the reader. [UPD: Oh, the steps are actually provided on pp. 107-108? Was I supposed to leaf ahead?]- In Chapter 3, we are using a dataset of movie choices to predict number of bathrooms for home-owner individuals - and include all available variables in our model. The authors could not be bothered to come up with a sensible prediction challenge, or to think about the model?Alas, this will have to do, as this seems to be the only book on SQL Server Data Mining. (I ignore the gnarled monstrosity published by Packt in 2014). And that is such a pity: an interesting, practical technology, clearly neglected by its creator.


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