Improving ETA Predictions with Advanced Deep Learning Arc...

What this episode covers

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/

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Frequently Asked Questions

How long is this episode of Snacks Weekly on Data Science?

This episode is 14 minutes long.

When was this Snacks Weekly on Data Science episode published?

This episode was published on July 22, 2024.

What is this episode about?

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,...

Can I download this Snacks Weekly on Data Science episode?

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