Speakers -> Bayesian Inference with Foursquare Data

QCon New York 2012 Speakers Schedule Tutorials Tracks Social Events Sponsors Registration Volunteers Venue Travel Hotels Video Calendar Follow Us Brought to you by Contacts Exhibit Sponsors General Information Registration Speakers	Presentation: "Bayesian Inference with Foursquare Data" Track: Solutions Track: Agile, DevOps, Data Processing Patterns Time: Monday 10:50 - 11:50 Location: Roebling/Gleason Abstract: Foursquare has an enormous database of Users and Locations. However, when not much is known about a specific user or a specific location, it becomes difficult to make inferences. How can we leverage a large data set in order to make educated guesses about the properties of specific data points which don't have much information associated with it? The approach covers Bayesian logic, Conjugate Priors, and belief propagation.		Max Sklar, Machine Learning Engineer, Foursquare Max Sklar is an engineer and a machine learning specialist. At Foursquare, his objective is to constantly make the application smarter and more interesting for users. Among these projects is improving Explore, which is Foursquare’s social recommendation system. His passion for recommender systems have led him to study how to make inferences with sparse information, and how to quantify uncertainty. This has lead to an interest in Bayesian methods in order to put a little common sense and intuition into data-based predictions. Prior to his position at Foursquare, Max contributed to the emerging location-based social space with the creation of Stickymap, which was a website that encouraged users to annotate a map with knowledge of their neighborhood. As an Adjunct Instructor at NYU, Max enjoys sharing his views on technology and computer science and sparking dialogue with the next generation of engineers. As an undergraduate, he was also a talk radio host on Yale Radio. Max holds an M.S. in Information Systems from NYU, and a B.S. in Computer Science from Yale.