/Flight-Fare-Prediction

Built flight fare prediction and deploy using flask on Heroku platform

Primary LanguageJupyter Notebook


Model deploy using Flask on Heroku Platform

https://flight-fare-prediction-kamal.herokuapp.com/


In this project I built a model for predicting the fare of the flight ticket.


What it does :

Live Demo

How it does :

Extract the dependent variables and the independent variables from the dataset. Split the skewed data into shuffled sets using stratified shuffle split in sklearn library. Used the Hyperparameter tuning to increase the accuracy of prediction.


Prerequisites :

  • Python
  • scikit-learn/sklearn
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Jupyter/Spyder/Pycharm

Dataset :

You can collect raw dataset from here. The files contain

  • Airline
  • Date_of_Journey
  • Source
  • Destination
  • Route
  • Dep_Time
  • Arrival_Time
  • Duration
  • Total_Stops
  • Additional_Info
  • Price

Model Pipeline :

Result :