Forecasting bike-share availability one hour ahead, continuously, on live open data — an end-to-end ML engineering showcase. Every prediction meets its ground truth an hour later.
Bikes available at one station: what the model said an hour in advance, what the persistence baseline said, and what actually happened.
Hourly mean absolute error across all stations — the model must stay below the baseline, or the weekly retrain won't promote it.