Maybe the business world has jumped the gun with all the talk about a looming skills shortage in big data and advanced analytics. There’s mounting evidence that it doesn’t take much to turn a novice programmer or statistician into a perfectly capable data scientist. Maybe all it takes is just some cheap cloud computing servers, or a few weeks studying machine learning with Stanford professor Andrew Ng on Coursera.
Much of this evidence comes via Kaggle, a platform where companies and organizations award prizes for the best solutions to their predictive-modeling needs. In September, for example, I covered a first-time Kaggle user and admitted data science neophyte named Carter S. who won a competition using a simple but effective method he dubbed “overkill analytics.”
Impressive, sure, but Carter builds insurance-industry risk models for a living. While he’s able to learn new techniques such as natural-language processing and social network analysis…
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