theraaajj/Algerian-Forest-Fire-Model

🔥 Algerian Forest Fire Prediction Model This project aims to predict the likelihood of forest fires in Algeria using machine learning techniques based on environmental and meteorological data. It includes model training, evaluation, and a simple web interface for user interaction. 📌 Project Overview Forest fires pose a major threat to the environment, biodiversity, and human life. By analyzing historical fire data from Algeria, this project builds a predictive model that can assist in early detection and help mitigate the impact of such disasters. The solution is backed by a machine learning model and deployed as a web application for easy access. 🧠 Features Predicts the likelihood of forest fire occurrence Based on temperature, humidity, wind speed, and other environmental features Clean and interactive web interface Trained machine learning model (e.g., logistic regression or decision tree) Jupyter notebooks for data exploration and model development 🧾 Directory Structure application.py – Main Python script to run the web app models/ – Serialized/trained ML model(s) notebooks/ – Jupyter notebooks for data analysis, preprocessing, and training templates/ – HTML templates for the Flask web interface requirements.txt – List of required Python libraries ⚙️ Tech Stack Language: Python Libraries: scikit-learn, pandas, numpy, Flask Data Visualization: matplotlib, seaborn Web Framework: Flask Deployment: Designed for easy deployment (Elastic Beanstalk support included) 🚀 How to Run Locally Clone the repository to your local machine Create and activate a virtual environment Install the dependencies listed in requirements.txt Run application.py to start the Flask web app Open your browser at localhost 📊 Dataset The dataset used in this project is the Algerian Forest Fires Dataset, which contains features like temperature, relative humidity, wind speed, rainfall, and fire occurrence labels. 🧪 Model Evaluation Models are evaluated using …