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I am curious to see if there is a conscise collection of success stories for a variety of machine learning approaches and how they have been applied to practical problems. I am not interested in the math as much as I am interested to see how people reasoned in matching a given real-world problem with a particular technique. If not general collection, I'd be interested to see at least specific techniques, i.e. single articles covering a single approach. Thanks |
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Have you looked into Machine Learning for Hackers? I have been scanning through the chapters and it covers a nice breadth of how to use Machine Learning algorithms, how to present the information so that it's usable, and all without too much concern for the math behind it all. Thanks Keith, it looks interesting, I'll check it out!
(Mar 27 '12 at 00:26)
Viktor Simjanoski
By the way, do you know of any other resources that are written in similar fashion, but that treat slightly more advanced techniques?
(Mar 28 '12 at 01:53)
Viktor Simjanoski
What kind of advanced techniques are you interested in? Edwin Chen wrote a really amazing blog post about unsupervised infinite mixture models which is certainly a good read on a more advanced topic.
(Mar 28 '12 at 01:59)
Keith Stevens
I don't mean cutting edge, but slightly more advanced than Machine Learning for Hackers, which is very basic. By slightly more advanced I mean things like HMM, graphical models, neural nets, in that realm, but given with very concrete examples in the style of 'Machine Learning for Hackers.'
(Mar 28 '12 at 14:05)
Viktor Simjanoski
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