Big Data and Math: Puzzlers Abound
December 14, 2015
Interested in math? Navigate to “Big Data’s Mathematical Mysteries: Machine Learning Works Spectacularly Well, but Mathematicians Aren’t Quite Sure Why.” Yep, I know the certainties of high school math are annoyances when dealing with more sophisticated procedures. Dabble in C* algebras, and you will realize why home economics and general business were appealing.
The point of the write up is that numerical recipes can do their thing on existing and incoming data. If the recipes were trained correctly by a human, some of the niftier systems can learn. Now this is not the same as housebreaking your new Great Dane, but the analogy is close enough for would be mathematicians.
If a system does not require humans to supervise it, methods exist to explore hidden structures. Think patterns a human cannot perceive.
Here’s the passage I highlighted:
These methods are already leading to interesting and useful results, but many more techniques will be needed. Applied mathematicians have plenty of work to do. And in the face of such challenges, they trust that many of their “purer” colleagues will keep an open mind, follow what is going on, and help discover connections with other existing mathematical frameworks. Or perhaps even build new ones.
The idea is that good enough mathematicians can use numerical procedures and get pretty useful outputs. There you go. No need to fool around with Hilbert spaces.
Stephen E Arnold, December 11, 2015
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Big Data and Math: Puzzlers Abound : Stephen E. Arnold @ Beyond Search