Less Mathematical Approaches to Machine Learning?

Posted by Ed on Stack Overflow See other posts from Stack Overflow or by Ed
Published on 2010-04-16T10:22:01Z Indexed on 2010/04/16 10:23 UTC
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Out of curiosity, I've been reading up a bit on the field of Machine Learning, and I'm surprised at the amount of computation and mathematics involved. One book I'm reading through uses advanced concepts such as Ring Theory and PDEs (note: the only thing I know about PDEs is that they use that funny looking character). This strikes me as odd considering that mathematics itself is a hard thing to "learn."

Are there any branches of Machine Learning that use different approaches?

I would think that a approaches relying more on logic, memory, construction of unfounded assumptions, and over-generalizations would be a better way to go, since that seems more like the way animals think. Animals don't (explicitly) calculate probabilities and statistics; at least as far as I know.

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