taxi-demand prediction model using deep learning
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Updated
Dec 3, 2018 - Jupyter Notebook
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taxi-demand
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Hourly taxi-order forecasting for Sweet Lift Taxi using LightGBM with lag features and rolling means (RMSE 39.7, target ≤ 48).
python data-science machine-learning time-series random-forest scikit-learn jupyter-notebook regression pandas lightgbm feature-engineering statsmodels demand-forecasting time-series-forecasting taxi-demand lag-features seasonal-decomposition
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Updated
May 1, 2026 - Jupyter Notebook
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