Capital Bikeshare DC
Analytics | Machine Learning
Built predictive models (XGBoost, Stacked Ensemble) to forecast hourly bike rental demand in Washington D.C., achieving the lowest RMSE among all tested models. Paired with Tableau visualizations to translate findings into actionable scheduling and marketing recommendations.
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