The 4th dimension: The Impact of Time on Machine Learning Systems

Human behavior is dynamic. From mood swings throughout the day to adopting different habits for each day of the week, time is an essential part of understanding changes in behavior. In this talk, we discuss the effect of time in machine learning systems that require understanding user behavior. We present ideas for keeping systems updated over time, methods to leverage time as a way to improve training data, and share lessons learned from studies and experiments conducted by Snap Research on the Snapchat platform.