I recently went to a presentation at the local Atlanta .NET Users’ Group on the Microsoft Kinect. The device has been one of the fastest selling game devices in history (a Guinness World Record for selling 8 million units in the first 60 days). The technology behind the device is based on machine learning algorithms.
The word “hacking” is actually inaccurate since Microsoft has been encouraging people to develop drivers. Kinect has a USB port, which allows the machine to be used with a regular computer. Nevertheless, there’s something edgy and dangerous about using the word “hacking” and when people talk about Kinect “development” (a comparatively boring and commercial word) the “hacking” term is sticking. I believe the gaming community likes the word “hacking”.
I see that the slides for the presentation I saw in March 2011 are not posted online. Thus, in this blog post I will have some comments on the device and some links to video. I will not be talking about the Kinect as a consumer game device, but I will have a link where you can explore that topic on your own.
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Data Mining with Microsoft SQL Server 2008 Review Chapter 7
Decision Trees is one of the most useful algorithms. This algorithm conceptually extends modeling into a tree of nested models where each branch provides tailored understanding of the training data. This blog posting will track the DMX code which substantially provides the discussion framework for the chapter. You can get this code for free from the authors’ (actually the publisher’s) website, but if you want to be a data mining professional you should also have the book. This same single algorithm encompasses both Microsoft Decision Trees and Microsoft Linear Regression.
The sample DMX code refers to the ASSprocs stored procedure. That code is available from http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470277742,descCd-DOWNLOAD.html. While I was looking for the code, I discovered that this book is available from Wiley in e-Book format (see the previous link), and optionally you can see the eBook as part of Safari Books Online (subscription service): http://my.safaribooksonline.com/9780470277744.
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