As domestic air travel is getting more and more popular these days in India with various air ticket booking channels coming up online, travellers are trying to understand how these airline companies make decisions regarding ticket prices over time. Nowadays, airline corporations are using complex strategies and methods to assign airfare prices in a dynamic fashion. These strategies are taking into consideration several financial, marketing, commercial and social factors are closely connected with the ultimate airfare prices. Due to the high complexity of the pricing models applied by the airlines, it is very difficult for a customer to purchase an air ticket at the lowest price, since the price changes dynamically. For this reason, several techniques ready to provide the proper time to the customer to buy an air ticket by predicting the airfare price, are proposed recently. The majority of those methods are making use of sophisticated prediction models from the computational intelligence research field known as Machine Learning (ML). In this machine learning in python project there is only one module namely, User. User can login with valid credentials in order to access the web application. A traveller can access this module to get the future price prediction of individual airlines. The prediction will help a traveller to decide a specific airline as per his/her budget. Single entries of current or previous data can be made. This training set is used to train the algorithm for accurate predictions.
- Traveler get the fare prediction handy using which it’s easy to decide the airlines.
- Saves time in searching / deciding for airlines.
- Improper data will result in incorrect fare predictions.