MDST – NFL Free Agency Value Prediction Competition Kick-Off – Nov. 9, 6pm

By | Data, Data sets, Educational, Events, Happenings, MDSTPosts, MDSTProjects, News

In this competition, student teams at the University of Michigan will use historical free agent data to predict the value of new contracts signed in the 2018 free agency period. These predictions will be evaluated against the actual contracts as they are signed. This competition is organized by the Michigan Data Science Team (MDST), in collaboration with the Baltimore Ravens and the Michigan Sports Analytics Society (MSAS).  Food will be provided. This is an initial kick-off meeting of the competition.

RSVP

Date, Time

Thursday, November 9 at 6:00 PM EST to Thursday, November 9 at 7:00 PM EST
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Location

Weiser Hall 10th Floor Auditorium
500 Church St, 48104, MI

Host

Michigan Data Science Team

 

 

Real estate dataset available to researchers

By | Data, Data sets, Educational, General Interest, Happenings, News

The University of Michigan Library system and the Data Acquisition for Data Sciences program (DADS) of the U-M Data Science Initiative (DSI) have recently joined forces to license a major data resource capturing parcel-level information about the property market in the United States.  

The data were licensed from the Corelogic corporation, who have assimilated deed, tax and foreclosure information on nearly all properties in the entire US. Coverage dates vary by county, some county records go back fifty years. Coverage is more comprehensive from the 1990s to the present.

These data will support a variety of research efforts into regional economies, economic disparities, trends in land-use, housing market dynamics, and urban ecology, among many other areas.

The data are available on the Turbo Research Storage system for users of the U-M High Performance Computing infrastructure, and via the University of Michigan Library.

To access the data, researchers must first sign a MOU; contact Senior Associate Librarian Catherine Morse cmorse@umich.edu for more information, or visit https://www.lib.umich.edu/database/corelogic-parcel-level-real-estate-data.