Mar 02

Just visit Kaggle is a platform for data prediction competitions that allows organizations to post their data and have it scrutinized by the world’s best data scientists. See how it works.

Who should host a competition on Kaggle?

Crowdsourcing data modeling is an effective way to build predictive algorithms. There are any number of approaches that can be applied to a data modeling problem, but it is impossible to know at the outset which will be most effective. A consultant or in-house statisitician can try a few, but opening up the problem to a wider audience ensures that organizations reach the frontier of what is possible from a given dataset.

Most data problems can be framed as a competition:

  • > banks predict which loan applicants are likely to default
  • > government treasuries forecast tax revenues
  • > websites make personalized product recommendations
  • > hedge funds crunch data to find trading opportunities
  • > bioinformaticians search for links between genetic markers and disease

Who should compete on Kaggle?

Data scientists rarely have access to real-world data. This is frustrating when you consider that many of the world’s organizations have piles of data that they can’t make the most of. Kaggle corrects this mismatch by giving data scientists access to real-world data and problems. Best of all, the burden of collecting, cleaning and structuring the data will have been done by others.

Competitions offer participants the opportunity to:

  • > try their techniques on real-world problems and receive real-time feedback
  • > enhance their reputations and win prizes
  • > meet and collaborate with new contacts
  • > improve their skills and help to rapidly progress the state of the art in a number of different fields

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