Flight Price Prediction Web App

This repository integrates Flask with a machine learning model to predict flight prices. The application allows users to input various features of a flight and receive an estimated price based on a trained machine learning model.

Demo

You can view the deployed application at the following link:

Flight Price Prediction App

Features

• User-friendly web interface built with Flask
• Input fields for flight parameters
• Real-time flight price predictions based on a machine learning model
• Deployed on Render for easy access

Installation

To install the required packages, run the following command in your terminal:

pip install -r requirements.txt

Usage

1. Clone the repository to your local machine:

   git clone https://github.com/anmol52490/flask-course-ml-project.git

2. Navigate to the project directory:

   cd flask-course-ml-project

3. Activate your virtual environment (if you have one):

   source venv/bin/activate   # On macOS/Linux
   .\venv\Scripts\activate    # On Windows

4. Run the Flask application:

   python app.py

5. Open your web browser and go to http://127.0.0.1:5000 to access the application locally.

Machine Learning Model

The model is trained on a dataset of flight prices and utilizes various features such as:

• Departure and arrival locations
• Flight duration
• Airlines
• Additional features relevant to pricing

The model's performance can be evaluated based on its accuracy and other metrics.

Requirements

The project requires the following Python packages, listed in requirements.txt:

• Flask
• scikit-learn
• pandas
• numpy
• gunicorn

Contributing

Feel free to contribute to this repository by submitting issues, suggestions, or pull requests.