Taxi-demand-forecasting-in-New-York-City

• Used the data set downloaded from Kaggle competition.
• Performed Data cleaning and analyzed the Yellow cab dataset in New York; studied the demand variations.
• Prepared data by clustering different regions of New York, smoothing time bins and visualized the clusters.
• Implemented regression algorithms like Linear Regression, Random Forest and XGBoost to achieved mean absolute percentage error (MAPE) of 0.125 with XGBoost algorithm.