This project aims to predict domestic flight fares in India using machine learning techniques. The dataset used for this project is the Domestic Flights Dataset in India from Kaggle, which contains information on various attributes of domestic flights such as source, destination, departure time, and other features.
Data pre-processing was done using encoding techniques to clean and process the data. Random Forest Regressor was used as a regression model and was hyperparameter tuned to improve the accuracy of the prediction. The final model was saved as a pickle file, which was used to create a Flask web app.
The web app provides a simple interface where users can input information about a domestic flight such as the source, destination, departure time, and other features. Based on the input, the app predicts the fare of the domestic flight using the trained model.
The app has been deployed on Heroku, and the project is open-source, and contributions are welcome