Machine Learning, Flight Price Predication Flight price can be something hard to guess, because prices are vary on the daily basis. We might have often heard travellers saying that flight ticket prices are so unpredictable.Here we take on the challenge! we are gonna prove that given the right data anything can be predicted. Here you will be provided with prices of flight tickets for various airlines between the months of March and June of 2019 and between various cities.
Size of training set: 10683 records
FEATURES: Airline: The name of the airline.
Date_of_Journey: The date of the journey
Source: The source from which the service begins.
Destination: The destination where the service ends.
Route: The route taken by the flight to reach the destination.
Dep_Time: The time when the journey starts from the source.
Arrival_Time: Time of arrival at the destination.
Duration: Total duration of the flight.
Total_Stops: Total stops between the source and destination.
Additional_Info: Additional information about the flight
Price: The price of the ticket