navya0203/flight-price-prediction

This project implements a flight price prediction algorithm using real-time data of Flight schedules across India.Here we have evaluated multiple ensemble machine learning techniques, optimizing the model with XGBoost and Random Forest algorithms to deliver high-performance predictive insights.

Flight Fare Prediction

Table of Contents

• About The Project
• Built With
• Getting Started
  • Prerequisites
  • Installation

About The Project

This project is a Flask web application that predicts the fare of flight tickets using machine learning algorithms. To estimate the price, the prediction model considers various factors such as departure date, arrival date, source, destination, stops, and airline preference.

Built With

This section should list any major frameworks/libraries that bootstrap your project.

• Flask
• Heroku
• Pandas
• Scikit-Learn

Getting Started

To get a local copy up and running, follow these simple steps.

Prerequisites

Before you begin, ensure you have Python installed on your machine. You can check your Python version with the following command:

python --version

Also, make sure pip, the Python package installer, is up to date:

pip install --upgrade pip

Installation

Clone the repository to your local machine:

git clone https://github.com/Navya0203/Flight-Price-Prediction.git

Navigate to the project directory and install the required Python packages:

pip install -r requirements.txt

Overview of the Website