09:00 - 10:00
‘From knowing what people do (events) using low-level sensor data from phones, Sentiance can find out why they are doing it (moments), when they’ll do it again and what type of people they are (segments). In this talk, I’ll explain the full machine learning pipeline used to assess a user’s driving behavior, including whether they were the driver or a passenger during a trip, which is a key component. We’ll look into detecting transport mode, map-matching GPS-fixes to a plausible traveling route, and fusing that data to arrive at the driver/passenger classifier, openly discussing all ML architectures used, from random forests to CNN/RNNs. After that, I’ll touch upon how moments and segments are derived. Expect a technical talk.