In this episode, we will discuss the importance of Estimated Time of Arrival (ETA) for DoorDash and how the company enhanced its machine learning model through three key directions: upgrading from a tree-based model to a deep-learning architecture, adopting a multi-task modeling approach, and leveraging probabilistic models.
For more details, you can refer to their published tech blog, linked here for your reference: https://doordash.engineering/2024/03/12/improving-etas-with-multi-task-models-deep-learning-and-probabilistic-forecasts/
