✈️ Flight Fare Predictor (Machine Learning)

Live Demo](https://flight-fare-predictor-machine-learning.onrender.com/) GitHub Repository

This web application predicts flight fares based on various input parameters such as airline, departure and arrival time, source, destination, duration, and number of stops. It uses a trained machine learning model to estimate prices, helping users plan their travel more efficiently.

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Features

• Predicts flight fare using real-time user inputs
• Trained using regression algorithms on actual flight fare data
• Clean and responsive web UI built with Flask
• Deployed and accessible online via Render

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Machine Learning Model

• Model Used: Random Forest Regressor (or specify if different)
• Training Data: Includes airlines, journey dates, stops, duration, source, and destination
• Techniques: Feature engineering, label encoding, one-hot encoding
• Model Evaluation: RMSE, R² Score (Add your actual results if available)

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Tech Stack

• Frontend: HTML5, CSS3, Bootstrap
• Backend: Python, Flask
• ML Libraries: Scikit-learn, Pandas, NumPy, Joblib
• Deployment: Render

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Screenshots *

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How to Run Locally

# Clone the repo
git clone https://github.com/RahulRajGiri15/Flight-Fare-Predictor__Machine-Learning
cd Flight-Fare-Predictor__Machine-Learning

# Install required packages
pip install -r requirements.txt

# Run the Flask application
python app.py

# Visit in your browser
http://127.0.0.1:5000/

Author

Made with ❤️ by Rahul Kumar Giri

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