Flight fare Prediction

The price of an Airline Ticket is affected by a number of factors, such as flight duration, days left for departure, arrival time and departure time etc. Airline organizations may diminish the cost at the time they need to build the market and at the time when the tickets are less accessible. They may maximize the costs. The price may rely upon different factors. Each factor has its own proprietary rules and algorithms to set the price accordingly. Recent advances in Artificial Intelligence (AI) and Machine Learning (ML) makes it possible to infer such rules and model the price variation.

Methodology:

Employed advanced techniques such as *data visualization, *Random Forest Regression, and *Hyperparameter Tuning .

Outcome:

Achieved accurate predictions of flight prices, empowering users to make informed choices for their travel plans