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Predicting Taxi Ride Duration (2019)

Tools: Python (numpy, pandas, matplotlib, seaborn), SQL, Jupyter Notebooks

  • Executed data science life cycle on 98,000-point dataset: data selection and cleaning, EDA, feature engineering, and model selection
  • Generated and fit linear regression model to predict travel time of a taxi ride in Manhattan
  • Implemented a tree regression model to increase accuracy of prediction decreased root mean square error by 43%