/Zainab Danish

How DoorDash Improves Holiday Predictions Via Cascade ML Approach tl;dr: DoorDash's engineering team tackled the challenge of accurately forecasting supply and demand during holidays, where traditional tree-based machine learning models like Random Forest and Gradient Boosting faced limitations. The article introduces the "cascade modeling approach" as a solution. This method extends the Gradient Boosting Machine model with a linear model to account for holiday impacts, enhancing forecast accuracy. The cascade approach involves calculating holiday multipliers, preprocessing data, and post-processing forecasts.

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