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MachineHack Data Science Challenge: Apply Machine Learning Skills to Predict Flight Prices
MachineHack Data Science Challenge: Apply Machine Learning Skills to Predict Flight Prices

MachineHack Data Science Challenge: Apply Machine Learning Skills to Predict Flight Prices

Published Updated

Key takeaways

  • MachineHack has launched a new hackathon focused on predicting flight ticket prices using machine learning.
  • Participants in the competition will analyse data to forecast fluctuations in flight ticket costs.
  • Winners will receive invitations to attend MachineCon, a premier analytics and machine learning conference in India.
  • The challenge addresses the inherent unpredictability of flight pricing, which can vary significantly over short periods.
5 min
Analytics India Magazine’s hackathon platform MachineHack, has come up with a new and challenging hackathon for data science enthusiasts. The new hackathon challenge is called Predict The Flight Ticket Price Hackathon, and the MachineHack users will have to predict a flight’s ticket prices based on the data given. The winners of the hackathon will win an invitation to the most exclusive analytics and machine learning conference in India, MachineCon. Flight tickets price 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. Huh! Here we take on the challenge! As data scientists, we are gonna prove that given the right data anything can be predicted. Here you will be provided with prices of tickets for various airlines among other features. You can participate in the hackathon by clicking here. 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 What are you waiting for? Get the data here and participate.
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