NYC Taxi Fare Prediction with 7 models (Linear Regression, Random Forest, XGBoost, LightGBM, CatBoost, KNN, and Decision Tree) The models used range from simple linear regression to more complex ensemble methods such as boosting algorithms. The aim was to improve prediction accuracy and handle categorical features efficiently.
