A total of 106 submissions were received for the inaugural Big Data Derby, a competition requiring entrants to provide a machine-learning model to analyze all manner of data regarding horse racing tactics, strategies and path efficiencies. Sponsored by the New York Racing Association and the New York Thoroughbred Horsemen's Association in partnership with the Kentucky Thoroughbred Association, Equibase, The Jockey Club, Breeders' Cup and the Thoroughbred Owners and Breeders Association, the Big Data Derby launched with a goal of better understanding the vast data set at hand to racing organizations, and to potentially develop new ways of racing and training in a highly traditional industry.
“Our main objective with this competition was to see if qualified data scientists could utilize horse-tracking data to improve the sport's collective knowledge in key areas such as equine welfare and performance,” said NYTHA President Joe Appelbaum.
The Big Data Derby offers a total of $50,000 in prize money with $20,000 awarded to the winner and $10,000 each to the next three placings. The competition is held on Kaggle, a global data science platform with over 500,000 active users where participants compete by using machine learning to solve problems ranging from the trivial to the extremely complex.
A judging committee will score the submissions based on four categories–Innovation [25 points], Relevance [30 points], Competence [25 points] and Presentation [20 points]. Winners will be announced in early December. For more information, click here.
The post Over 100 Submissions for Inaugural Big Data Derby appeared first on TDN | Thoroughbred Daily News | Horse Racing News, Results and Video | Thoroughbred Breeding and Auctions.
