princekumar8212/Algerian-Forest-Fire-Prediction

End-to-end machine learning project for predicting the Fire Weather Index (FWI) using Linear Regression, exploratory data analysis, and feature engineering. # 🌲 Algerian Forest Fire Prediction using Machine Learning An end-to-end machine learning project that predicts the **Fire Weather Index (FWI)** using meteorological and environmental data from the Algerian Forest Fires dataset. The project covers the complete data science workflow, including data cleaning, exploratory data analysis (EDA), feature engineering, model training, and performance evaluation using Linear Regression. --- # 📌 Project Overview Forest fires pose a significant threat to ecosystems, wildlife, and human life. Accurate prediction of fire severity enables authorities to implement preventive measures and allocate resources effectively. This project leverages historical weather data to build a machine learning model that predicts the **Fire Weather Index (FWI)**, an important indicator used to estimate the potential intensity of forest fires. --- # 🎯 Business Problem Early prediction of forest fire risk helps government agencies and environmental organizations: - Identify high-risk areas. - Improve disaster preparedness. - Support efficient resource allocation. - Minimize environmental and economic losses. - Assist in decision-making for wildfire prevention. --- # 📊 Dataset The dataset contains meteorological observations collected from two regions in Algeria: - Bejaia Region - Sidi Bel-Abbes Region ### Features include: - Temperature - Relative Humidity (RH) - Wind Speed (Ws) - Rainfall - FFMC - DMC - DC - ISI - BUI - FWI (Target Variable) --- # 🛠 Tech Stack - Python - Jupyter Notebook - Pandas - NumPy - Matplotlib - Seaborn - Scikit-learn --- # 📂 Project Structure ```text Algerian-Forest-Fire-Prediction/ │ ├── data/ │ ├── raw/ │ │ └── Algerian_forest_fires_dataset_UPDATE.csv │ │ │ └── processed/ │ └── Algerian_forest_fire_clean_newdata.csv │ ├── notebooks/ │ ├── Data_Cleaning_and_Preprocessing.ipynb │ └── Algerian_Forest_Fire_Predicti …