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flight-prices

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A comprehensive project analyzing airline flight data to predict flight prices using machine learning models. The project covers data cleaning, exploratory data analysis (EDA), feature engineering, model building, and evaluation, with potential for deployment.

  • Updated Sep 25, 2024
  • Jupyter Notebook

Flight pricing is dynamic and influenced by various factors—duration, stops, airline, time of booking, etc. This project challenges you to uncover trends in airfare and how different flight attributes impact pricing. Utilize your skills in EDA, SQL, and statistics to derive meaningful insights.

  • Updated Aug 10, 2025
  • Jupyter Notebook

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. This is the reason why flight prices are quiet unpredictable. Data consisting of several details and prices of flight tickets for various airlines between the months of March and June of …

  • Updated Nov 3, 2020

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