rushxbh910/FireRisk-AI

This project predicts the Fire Weather Index (FWI) using machine learning on the Algerian Forest Fires Dataset. It includes feature engineering, EDA, and model training to assess wildfire risk based on weather conditions. The project showcases expertise in data preprocessing, model optimization, and performance evaluation. 🚀 # 🔥 Algerian Forest Fires – Fire Weather Index (FWI) Prediction This project predicts the **Fire Weather Index (FWI)** using machine learning models trained on the **Algerian Forest Fires Dataset**. It includes data cleaning, feature engineering, exploratory data analysis (EDA), model training, and a deployed web app that allows users to estimate wildfire risk based on current weather and fuel conditions. --- ## 📌 About the Project > Predicting wildfire intensity is essential for disaster prevention and environmental safety. > This project demonstrates proficiency in: - Feature engineering - Model optimization - Web deployment - Real-world data processing 🚀 The final model can be accessed via a web interface built using **Flask**, with a stylish frontend and robust backend predictions. --- ## 📚 Table of Contents - Demo - Features - Tech Stack - Installation - Usage - Project Structure - Example Prediction - License --- ## 🖥️ Demo > 🎯 Enter values for **Temperature**, **Humidity**, **Rain**, etc. → click **Predict 🔥** → receive real-time FWI prediction! --- ## ✅ Features - 📊 EDA of Algerian Forest Fire Dataset - 🔍 Feature Engineering and Cleaning - 🤖 Machine Learning with Ridge Regression - 🧠 Model evaluation and optimization - 🌐 Interactive Flask Web App - 🗃️ Includes trained model (`ridge_model.pkl`) and scaler (`scaler.pkl`) - 📈 Input fields for user-defined predictions --- ## 🧰 Tech Stack | Layer | Technology | |--------------|----------------------------------------| | Language | Python 3 | | Data | Pandas, NumPy | | ML Models | Scikit-learn (Ridge Regression) | | Visuals | Matplotlib, Seaborn | | Web Backend | Flask | | Frontend | HTML, CSS (Bootstrap 5) | --- ## ⚙️ Installation ### Clone the Repository ```bash git clone github.com …