An Introduction to Machine Learning with Web Data is a new video offering from O’Reilly with data scientist Hilary Mason delivering the content in seminar format.   At slightly under three hours in length, broken into five segments, the video is a well-paced primer for those new to machine learning.

The example case used is classification of article data retrieved from the New York Times, using Python and various algorithms.  Python 2.x and several modules are used for this purpose, so to follow along you should have access to a machine with that version of Python and the ability to install modules.  Code used in the seminar is available for checkout using git, via Github.  After installing the appropriate Python modules, the provided scripts functioned without errors.    Some experience with Python would make the experience better, but the code is not complex and could be worked out by most programmers.

While the use of mathematics is crucial to analysis, the math used in this presentation is easily understood and contributes to the content ( a positive feature unusual enough to rate high praise ).

Overall this would be a worthwhile purchase for someone interested in machine learning, but who does not have much, if any, hands-on experience with the processes involved.


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