GigaOm, By Derrick Harris, Jun 6, 2012.
Kaggle is now letting its stable of expert data scientists compete to tell companies how they can improve their businesses with machine learning. It's part of a natural evolution of Kaggle from a plucky startup to an IT company with legs, but it's actually more like a prequel to Kaggle's flagship predictive modeling competitions than it is a sequel.
... The way Kaggle Prospect works is rather simple: Customers submit a sample of the data they want to better analyze, and competitors play around with the data and propose ideas on how to best use it. When the competition deadline comes, a winner is selected by some combination of community voting and customer selection. Customers pay their fee to Kaggle and the reward to the winner, and are free to do what they want with the advice.
... Howard said this process is part of the "analytics value chain" that Kaggle hopes to create as its own business model matures. Companies can use the platform to figure out how to best use their data, then build and train their models, figure out how to implement them in production and at scale, and finally maintain and improve them. "You have to get everything right in order to actually leverage your data," he said, and Kaggle wants to help at every step.
Kaggle Prospect is an open data exploration and problem identification platform that lets organizations with large datasets solicit proposals from the best minds in our 40,000 strong community of predictive modeling and machine learning experts. The experts will peer-review each others ideas' and we'll present you with the short list of what problems your data could answer.
If you are sitting on a gold mine of data, but aren't sure where to start digging, Kaggle Prospect is the place to start.