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This is a sample end to end implementation of flight fare price prediction machine learning project. Using the EaseMyTrip website data set on kaggle, I trained a Random Forest Regressor to predict the flight fare prices (in Indian Rupee) between source and destination cities based on a rich array of feature variables such as date and time of arrival and departure, date of search, layovers and the corresponding flight carriers. A fair bit of data preparation was needed due to the variety in the data types of the feature variables. Please visit my github to view the source files and the accompanying jupyter notebook.