ADDY-IN/Algerian-Forest

🌲🔥 Algerian Forest Fire Prediction 🔥🌲 📌 Overview Algerian Forest Fire Prediction is a machine learning project that aims to predict the likelihood of forest fires in Algeria based on environmental factors. By leveraging advanced machine learning models, this project helps in taking preventive measures and ensuring early fire detection to protect forests and wildlife. 🌍🌿 🚀 Features ✅ Predicts fire occurrence based on environmental data 📊 ✅ Uses machine learning algorithms for accurate predictions 🤖 ✅ Dataset sourced from Algerian forest regions 🌎 ✅ Provides visual insights into fire patterns 🔥 ✅ Helps in making data-driven decisions for fire prevention 🛑 📂 Dataset The dataset consists of meteorological and environmental factors that influence forest fires in Algeria. Key attributes include: 🌡️ Temperature (°C) 💨 Relative Humidity (%) 🌬️ Wind Speed (km/h) ☀️ Rainfall (mm) 🔥 Fire Occurrence (Yes/No) 🛠️ Tech Stack 🔹 Python 🐍🔹 Pandas & NumPy for data processing 📊🔹 Matplotlib & Seaborn for visualization 📉🔹 Scikit-learn for machine learning models 🤖🔹 Flask (if deployed as an API) 🌐 📜 Installation Guide To set up the project on your local machine, follow these steps: # Clone the repository $ git clone github.com # Navigate to the project directory $ cd Algerian-Forest # Create a virtual environment (Optional but recommended) $ python -m venv env $ source env/bin/activate # For Linux/Mac $ env\Scripts\activate # For Windows # Install dependencies $ pip install -r requirements.txt 🏃‍♂️ How to Run After installation, you can run the model or API: # Run the prediction script $ python predict.py # If using Flask for API deployment $ python app.py 📊 Model Performance The model has been trained using supervised learning algorithms, including: ✔ Random Forest Classifier 🌲✔ Logistic Regression 📈✔ Support Vector Machine (SVM) 🔍✔ CatBoost 🏆 📌 Future Enhancements 🔜 Deploy the model as a web app 🌐🔜 Improve model accur …