Join us at meetup for the MIT Big Data Challenge - Transportation in the City of Boston.
MEETUP: TUESDAY DEC 10 5:00-7:00pm
LOCATION: Stata Center, 32-G882, Hewlett Meeting Room
Come learn more about the Challenge and meet other students passionate about using big data for good!
Hear from and connect with:
-- Professor Sam Madden, CSAIL, co-Director MIT Big Data Initiative
-- Eugene Wu, CSAIL, Big Data Challenge team/Data expert
-- Kris Carter, Mayor's Office
-- Chris Osgood, Mayor's Office of New Urban Mechanics
-- Curt Savoie, Principal Data Scientist, City of Boston
We will kick off at 5pm with short Introduction to the Challenge talking about Motivation and the Data. Followed by pizza, chance to ask questions and meet others working on the challenge. Learn about and discuss relevant MIT IAP session classes/tutorials being held in JAN 2014.
This will be an excellent opportunity to connect with other students, form teams, ask questions and learn about tools.
So we know how many pizza's to order - register for Dec 10 meetup here: https://www.eventbrite.com/e/mit-big-data-challenge-meetup-tickets-9532175995
About the Challenge:
OPEN: NOV 12 2013
END: JAN 20, 2014
PRIZES: totaling $10K
The first MIT Big Data Challenge launched November 12 2013 in partnership with the City of Boston and co-sponsored by Transportation@MIT focuses on transportation in downtown Boston. The challenge will make available multiple data sets, including transportation data from more than 2.3 million taxi rides, local events, social media and weather records, with the goal of predicting demand for taxis in downtown Boston and creating visualizations that provide new ways to understand public transportation patterns in the city.
The City of Boston is interested in gaining new insights into how people use all modes of transportation travel in and around the downtown Boston area. A critical imperative of Boston's Complete Streets Policy is to move all modes of transportation more efficiently and to use real-time data to facilitate better trip-planning between modes of transportation. With urban congestion on the rise, city planners are looking for ways to improve transportation such as providing people with more options to get from one place to another (walking, biking, driving, or using public transit) and by reducing and more efficiently routing vehicles in the city.
This Big Data Challenge provides a unique opportunity to analyze City of Boston taxi data and combine multiple data sets including social media, transit ridership, events data and weather data to effectively predict demand and better understand patterns in taxi ridership. We hope this will result in new insights for the City of Boston and the public that will improve transportation in the city (and ability to get a cab when you need one)!