DeyApurba/____Algerian_Forest_Fires_Prediction_Using_Regression__

# 🌲 Algerian Forest Fire Prediction – ML Powered Flask App This ML project predicts the likelihood of forest fires in Algeria using weather-related data. This project includes full-cycle ML development: data preprocessing, exploratory data analysis (EDA), feature engineering, model training, evaluation, and deployment via Flask. --- ## 📌 Key Highlights - ✅ End-to-End ML Pipeline (EDA → FE → Model → Deployment) - 🔥 Predicts fire occurrence in two Algerian regions - 🧪 Trained using Random Forest Classifier (or your actual model) - 🧠 Model serialized using `pickle` - 🌐 Flask Web Interface for real-time predictions --- ### 📊 Evaluation Metrics The models were evaluated using: - **Mean Absolute Error (MAE)** - **R² Score** ---- # App Screenshot (1st Input, 2nd Result) --- ## 🧠 Technologies Used - Python 3.x - Pandas, NumPy - Seaborn, Matplotlib - Scikit-learn - Flask --- ## 📁 Project Structure ```plaintext 📦 Algerian Forest Fire Prediction ├── static/ # Static files (CSS, images) ├── templates/ # HTML templates │ └── index.html # Main UI ├── model.pkl # Trained ML model ├── app.py # Flask app ├── requirements.txt # Required packages ├── Cleaned And Algerian Forest Fires Update dataset.ipynb # EDA & Feature Engineering ├── Model Training.ipynb # Model training └── README.md --- ## 📊 Dataset The dataset is based on Algerian forest fire records and includes weather-related features. Source: UCI Machine Learning Repository ---