by Angela Guess
Lisa Morgan recently wrote in Information Week, “The data science talent shortage has some companies thinking outside the box. Even if your company employs a formidable data science team, you would likely still benefit from third-party ideas or solutions. Data science competitions and other forms of crowdsourcing offer viable means of advancing the art of the possible relatively quickly and cost-effectively. We share some of the possibilities.”
Morgan gives the example of Booz Allen Hamilton: “Top-tier data science talent is hard to find. Booz Allen Hamilton has plenty of such talent in-house, and it has teamed up with Kaggle on competitions for the past two years. This year’s competition, the Second Annual Data Science Bowl, aims to transform the diagnosis of heart disease. The competition, which is active at the time of this writing, offers a $200,000 prize. A total of 525 teams are participating.”
Morgan offers another possibility: “The research community’s motto historically has been “publish or perish,” but it can take many years before the research is published, cited, and adopted by a community. Competitions are a fast way of publicizing research and encouraging contributions to the body of research. ‘If you run a competition that’s judged on the accuracy of your algorithm, there’s no ambiguity,’ said Goldbloom. ‘Machine learning researchers have noticed this is a good way to get their work recognized. It’s a good way to drive the adoption of a machine learning technique’.”
photo credit: Flickr/ lumaxart