This repository represents the work completed for a data analytics capstone project that aims to predict the demand for ride-hailing services (i.e., Lyft and Uber) in the City of Toronto using regression, time series, and geospatial analysis techniques.
The repository is divided into subfolders:
data_explore- Provides an in-depth exploration of the ridehailing and weather datasetsanalysis_pred- Provides further analysis to support data cleaning, test different time-series modelling methods, and predict ridehailing trip demandfinal_report_code- Identififes the optimal method to predict demand for ride-hailing services
Matthew Lee [email protected]