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!

1. Machine Learning and
Big Data at Foursquare
Blake Shaw, PhD
Data Scientist @ Foursquare
@metablake

3. What is foursquare?
An app that helps you
explore your city and
connect with friends
A platform for location
based services and
data

4. 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

5. What is foursquare?
Mobile Social
Local

6. Stats
10,000,000+ people
25,000,000+ places
1,000,000,000+ check-ins
10,000+ actions/second

7. Growth

8. Growth

9. Growth

10. 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

11. Recommendation engine
• foursquare explore
provides realtime
recommendations using:
• location
• time of day
• check-in history
• friends preferences
• venue similarities

12. Signals about places

13. Networks of people

14. Networks of people
Brooklyn
Manha-an
SF
Australia

15. 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?

16. Our data stack
• MongoDB
• Amazon S3, Elastic Mapreduce
• Hadoop
• Hive
• Flume
• R and Matlab

17. Join us!
foursquare is hiring!
85+ people and growing
foursquare.com/jobs
Blake Shaw
@metablake
blake@foursquare.com