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Published on Jul 31, 2015
The presentation is to show how Airbnb's Trust and Safety team has built machine learning infrastructure from the ground up to catch and defuse fraudsters on the platform. This talk will briefly go through the history of the machine learning platform from its very basic roots to the advanced system that is in place today. We find that by taking a tightly coupled, naïve implementation to a well-factored, cleanly separated systems, we can individually tune each component to decrease the cycle between bad behavior to well-performing model to catch said behavior, and how we could leverage that introspection to enable realtime detection of issues at scale. Further, by empowering data science to explore new features independently from engineering efforts, we are able to reduce the time from feature conception to production implementation.