NIJ crime forecasting challenge

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NIJ's Real-Time Forecasting Challenge

If you want to show off your forecasting chops, and maybe even make a little money, the National Institute of Justice has just the challenge for you. The NIJ's Real-Time Crime Forecasting Challenge:

...seeks to harness the advances in data science to address the challenges of crime and justice. It encourages data scientists across all scientific disciplines to foster innovation in forecasting methods. The goal is to develop algorithms that advance place-based crime forecasting through the use of data from one police jurisdiction.

A total of $1.2 million is being awarded across three contestant types:

  • Large Business Contestants: 40 prizes of $15,000 each for a total prize of $600,000.
  • Small Team/Business Contestants: 40 prizes of $10,000 each for a total prize of $400,000.
  • Student Contestants: 40 prizes of $5,000 each for a total prize of $200,000.

Full details are available on the forecast challenge website, and you can register for an information webinar on October 6, at 1pm ET.

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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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