Deepakshukla241999/testforestfire

It is machine learning project. That predict fire in forest based on algerian forest fire data. # 🔥 Forest Fire Prediction Web Application A machine learning-based web application that predicts **forest fire-related values** using environmental and fire-weather indices. The application uses a trained **Ridge Regression** model and a **StandardScaler** for preprocessing, with a **Flask** web interface for taking user inputs and displaying predictions. --- ## 📌 Project Overview Forest fires can cause significant environmental and economic damage. Predicting fire-related conditions using weather and fire-weather indicators can help in early assessment and monitoring. This project implements a **machine learning regression model** that takes environmental parameters as input and predicts the target fire-related value. The trained model is integrated into a **Flask web application**, allowing users to enter the required parameters through a web form and receive predictions in real time. --- ## ✨ Features * 🔥 Forest fire prediction using Machine Learning * 📊 Uses environmental and fire-weather parameters * 🤖 Ridge Regression model * ⚙️ Feature standardization using `StandardScaler` * 🌐 Flask-based web application * 📝 HTML form for user input * ⚡ Real-time prediction * 💾 Pre-trained model and scaler stored using Pickle * 🚀 Can be deployed as a web application --- ## 🛠️ Technologies Used | Technology | Purpose | | ---------------- | ---------------------------------- | | Python | Programming language | | Flask | Web application framework | | Scikit-learn | Machine learning and preprocessing | | Pandas | Data manipulation | | NumPy | Numerical operations | | Ridge Regression | Prediction model | | StandardScaler | Feature normalization | | HTML/CSS | Frontend | | Pickle | Model serialization | --- ## 🧠 Machine Learning Model The proj …