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citibikenyc

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Developed statistical models with data visualizations to provide solution recommendations for the client. Performed data cleaning using Pandas and NumPy to ensure the correctness and completeness of the dataset and create effective visualizations to help the audience derive greater insights

  • Updated Jun 30, 2021
  • Jupyter Notebook

End-to-end ML pipeline predicting Citi Bike ride cost differences under varying weather conditions. Built on 1M NYC/NJ trips using XGBoost, AWS, geospatial API, Meteostat API, and DistanceMatrix AI. M.S. thesis project — CSUSB 2026.

  • Updated Jun 25, 2026
  • Jupyter Notebook

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