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This is a Machine Learning model which helps us to predict the Flight Fare price created using Flask HTML CSS BOOTSTRAP

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FlightFarePrediction

Project Structure

This project has four major parts :

  1. model.py - This file contains the code for our ML model
  2. app.py - This file contains our flask API
  3. templates - This folder contains the HTML templates
  4. static - This folder contains the .css file and the images for the html file index.html to use and render a good looking web-app.

Guide

  1. The project should be in the main directory.Run the following command to the Machine Learning model
python model.py
  1. Run app.py using below command to start Flask API
python app.py runserver

By default, flask will run on port 5000.

  1. Navigate to URL http://127.0.0.1:8000/ (This local server will be assigned after you run the unicorn command)

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This is a Machine Learning model which helps us to predict the Flight Fare price created using Flask HTML CSS BOOTSTRAP

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  • Jupyter Notebook 83.2%
  • HTML 8.1%
  • CSS 4.7%
  • Python 4.0%