sarbkk28/Algerian-Forest-Fire

🔥 Algerian Forest Fire FWI Prediction Web App This project is a Flask-based web application that predicts the Fire Weather Index (FWI) using a Machine Learning model trained on the Algerian Forest Fires Dataset. Users can input environmental parameters (temperature, humidity, wind speed, etc.) through a web form and get a predicted FWI value instantly. 📌 Features Web interface built with Flask Machine Learning model (Ridge Regression) Input multiple weather and fire-related parameters Predicts Fire Weather Index (FWI) Simple and clean UI Easy to run locally 🧠 Machine Learning Model Algorithm: Ridge Regression Dataset: Algerian Forest Fires Dataset Preprocessing: Standard Scaling Features used: Temperature RH (Relative Humidity) Ws (Wind Speed) Rain FFMC DMC ISI Classes Region Algerian Forest fire/ │ ├── models/ │ ├── application.py │ ├── ridge.pkl │ ├── scaler.pkl │ ├── templates/ │ │ └── index.html │ ├── requirement.txt │ ├── model train.ipynb │ └── eda fe algerian forest fire.ipynb │ └── README.md ⚙️ Installation & Setup 1️⃣ Clone the repository git clone github.com cd algerian-forest-fire-flask-app 2️⃣ Create virtual environment (optional but recommended) python -m venv venv venv\Scripts\activate 3️⃣ Install dependencies pip install -r requirement.txt 4️⃣ Run the Flask app cd models python application.py 5️⃣ Open in browser 127.0.0.1 🛠 Technologies Used Python Flask NumPy Pandas Scikit-learn HTML Git & GitHub 🚀 Future Improvements Add better UI styling (CSS / Bootstrap) Deploy on Heroku / Render Add input validation Add graphs and visualization Convert into REST API