HetalBagal/End-to-End-ml-forest-fire-project

This project demonstrates end-to-end machine learning model training using the Algerian Forest Fires dataset, including data cleaning, EDA, feature engineering, and model building. # 🔥 Algerian Forest Fire Prediction - ML Project ## 📌 Overview This project focuses on building a Machine Learning model to predict forest fires using the Algerian Forest Fires dataset. It includes: - Data Cleaning - Exploratory Data Analysis (EDA) - Feature Engineering - Model Training - Model Saving ## 📊 Dataset The dataset contains meteorological data and fire weather indices. ## ⚙️ Technologies Used - Python - Pandas - NumPy - Matplotlib - Seaborn - Scikit-learn ## 📈 Workflow 1. Data Cleaning 2. Exploratory Data Analysis 3. Feature Engineering 4. Model Training (Ridge Regression) 5. Model Evaluation 6. Model Saving using Pickle ## 📌 Results The model successfully predicts fire weather index values based on input features. 💡 Future Improvements Try other models (Random Forest, XGBoost) Deploy using Flask or Streamlit Add UI for prediction