Machine Learning and Big Data at Foursquare

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At foursquare, we believe there is a huge opportunity to apply machine learning algorithms to the collective movement patterns of millions of people and build new services which help people better understand and connect with places.

Foursquare is now aware of 25 million places worldwide, each of which can be described by unique signals about who is coming to these places, when, and for how long. We employ a variety of machine learning algorithms at foursquare to distill these signals into useful data for our app and our platform.

In the slides below, we talk briefly about the data at foursquare and some interesting applications of machine learning. Enjoy!

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Machine Learning and Big Data at Foursquare

  1. 1. Machine Learning andBig Data at FoursquareBlake Shaw, PhDData Scientist @ Foursquare@metablake
  2. 2. What is foursquare? An app that helps you explore your city and connect with friends A platform for location based services and data
  3. 3. What is foursquare? People use foursquare to: • check in to places • discover new places • share w/ friends • get tips about places • get deals • earn points and badges • keep track of visits
  4. 4. What is foursquare?Mobile Social Local
  5. 5. Stats10,000,000+ people25,000,000+ places1,000,000,000+ check-ins10,000+ actions/second
  6. 6. Growth
  7. 7. Growth
  8. 8. Growth
  9. 9. Learning with location data• Check-ins are a rich source of data that describe human behavior• We apply machine learning algorithms to the collective movement patterns of millions of people to build exciting new services
  10. 10. Recommendation engine• foursquare explore provides realtime recommendations using: • location • time of day • check-in history • friends preferences • venue similarities
  11. 11. Signals about places
  12. 12. Networks of people
  13. 13. Networks of peopleBrooklyn Manha-an SF Australia
  14. 14. Open questions• How to measure similarity between people and places?• How to determine influence in large networks of people and places?• What statistics can we use to describe people’s behavior in the real-world?• How do we predict what information will be timely and relevant to a user?
  15. 15. Our data stack• MongoDB• Amazon S3, Elastic Mapreduce• Hadoop• Hive• Flume• R and Matlab
  16. 16. Join us!foursquare is hiring!85+ people and growingfoursquare.com/jobsBlake Shaw@metablakeblake@foursquare.com

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