abhijitpadhi1/ModelBuilding_demo

Algerian Forest Fires Prediction is a simple but complete machine learning project designed to predict the likelihood of a forest fire based on meteorological and environmental parameters. Note: This is an experimental project created to explore the process of machine learning model building and deployment. # 🌲 Algerian Forest Fires Prediction 🔥 > ⚠️ **Note:** This is an **experimental project** created to explore the process of **machine learning model building and deployment**. --- ## 📑 Table of Contents - 📌 Project Overview - 📁 Project Structure - 📊 Dataset Description - ⚙️ Installation & Setup - 🚀 Usage - 🧠 Machine Learning Workflow - 🛠️ Tech Stack - 📈 Future Improvements - 📜 License - 👨‍💻 Author --- ## 📌 Project Overview **Algerian Forest Fires Prediction** is a simple but complete **machine learning project** designed to **predict the likelihood of a forest fire** based on meteorological and environmental parameters. This project demonstrates: - ✅ End-to-end ML pipeline (EDA → Feature Engineering → Model Training → Deployment) - 🌐 Building and serving a prediction API using Flask - ☁️ A simple, interactive web interface for real-time predictions. --- ## 📁 Project Structure ``` ├── .ebextensions/ # AWS Elastic Beanstalk deployment configs (optional) ├── Notebooks/ │ ├── 2.0-EDA And FE Algerian Forest Fires.ipynb # Data exploration and feature engineering │ └── 3.0-Model Training.ipynb # Model training and evaluation ├── data/ │ ├── Algerian_forest_fires_cleaned_dataset.csv # Cleaned dataset │ └── Algerian_forest_fires_dataset_UPDATE.csv # Original dataset ├── models/ │ ├── ridge.pkl # Trained ML model │ └── scaler.pkl # Data scaler for preprocessing ├── static/ │ ├── style.css # Stylesheet for the web interface │ └── script.js # JavaScript for asynchronous predictions ├── templates/ │ └── home.html # Web interface homepage ├── .gitignore # Git ignore file ├── application.py # Flask application ├── requirements.txt # …