Case Study

To achieve the project’s goal of analyzing historical domestic flight prices and developing a predictive model for future prices, we used statistical analysis techniques to identify patterns and trends in the data. We also used machine learning algorithms to develop a predictive model that can accurately forecast future prices based on historical data and other relevant factors. The model was tested and refined using cross-validation techniques to ensure accuracy and reliability. Finally, we presented our findings in a clear and concise manner, along with recommendations for airlines, travelers on how to use this information to make more informed decisions.