sandyds-ml / flight-price-prediction

Flight Price Prediction

Problem Statement: Flight ticket prices can be something hard to guess, today we might see a price, check out the price of the same flight tomorrow, it will be a different story. We might have often heard travellers saying that flight ticket prices are so unpredictable. 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

Size of test set: 2671 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

You have to use your skills as a data scientist and build a machine learning model to predict the price of the flight ticket.

Note: You can find the dataset in the link below.

Downlaod Files: https://github.com/dsrscientist/Data-Science-ML-Capstone-Projects