How DoorDash Built an Ensemble Learning Model for Time Series Forecasting

In real-world forecasting applications, it is a challenge to balance accuracy and speed. We can achieve high accuracy by running numerous models and configuration combinations and we gain speed through running fast, computationally inexpensive models. We explore a number of models and configuration combinations at DoorDash to forecast demand on our platform. However, the challenge ... The post How DoorDash Built an Ensemble Learning Model for Time Series Forecasting appeared first on DoorDash E...

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