I have created this project where we predict the airline fare for a particular date of travel. Basically the user has to input all the details of travel like date, month, airline company, Departure, Arrival, and number of stops.
Many people, travel through Airline first time or rarely and end up paying a lot more than the actual price. Using this I plan to give the user a predicted price of the airline fare, so that they can plan much in advance and end up paying less money.
Airline price, is very volatile and based upon many factors such as fuel price, demand, etc. That's why I have made use of historical Airline data using which I have trained my machine learning model.
I have made use of Random Forest Regressor model as it had given the best accuracy among all the other models I have implemented in this project.
In this project, I have made use of Python 3 Programming Language and have made use of pandas, numpy, matplotlib, seaborn and sklearn for the data science and machine learning part.
I have for the frontend made use of Flask framework.
For more info on the libraries, please refer the requirement.txt file.
I have used the dataset from kaggle - https://www.kaggle.com/datasets/absin7/airlines-fare-prediction