rajan7838/Algerian-Forest-Fire-Prediction

# Algerian Forest Fire Prediction ### Project Overview This is a Machine Learning web application that predicts the **Fire Weather Index (FWI)** for Algerian forests. The model is built using a Ridge Regression algorithm to help authorities predict fire risks based on environmental factors. ### Technical Stack * **Language:** Python 3.8 * **Web Framework:** Flask * **Machine Learning:** Scikit-Learn (Ridge Regression) * **Data Handling:** Pandas, NumPy * **Frontend:** HTML5 with Jinja2 templates ### Project Structure * `application.py`: The main Flask entry point. * `model/`: Contains the trained `ridge.pkl` and `scaler.pkl` files. * `notebooks/`: Data cleaning and model training experiments. * `templates/`: HTML files for the user interface. * `requirements.txt`: List of required Python libraries. ### How to Run Locally 1. Clone the repository: `git clone github.com` 2. Install dependencies: `pip install -r requirements.txt` 3. Run the application: `python application.py`