January 17 to 19 2018, Santa Clara, USA.


Speaker "Ankit Jain" Details

Name :
ankit jain
Company :
Title :
Data Scientist
Topic :

Personalization using LSTMs

Abstract :

Personalization is a common theme in social networks and e-commerce businesses. However, personalization at Uber will involve understanding of how each driver/rider is expected to behave on the platform. One way to quantify future behavior is to understand the amount of trips a driver/rider will do. In this talk, I will present our work on training LSTMs for short term trip predictions (4-6 weeks) of each driver on the platform. Specifically, I would like to describe how we combine past engagement data of a particular driver with incentive budgets and use a custom loss function (i.e. zero inflated poisson) to come up with accurate trip predictions using LSTMs. Predicting rider/driver level behaviors can help us find cohorts of high performance drivers, run personalized offers to retain users, and deep dive into understanding of deviations from trip forecasts.

Profile :
Ankit currently works as a Data Scientist at Uber where his primary focus is on forecasting and self driving car's business problems.Prior to that, he has worked in a variety of data science roles at Runnr, Facebook, BofA and Clearslide. Ankit holds a Masters from UC Berkeley and BS from IIT Bombay (India).

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