namanbhattt07/end-to-end-ml-project

Algerian forest fire project (just for practice) Author : Naman Bhatt ``` # End-to-End Machine Learning Project – Forest Fire Prediction This is an end-to-end Machine Learning project built using Python and Flask. The application predicts the **Fire Weather Index (FWI)** based on multiple environmental and weather parameters. --- ## Project Overview This project demonstrates the complete Machine Learning workflow starting from data preprocessing and exploratory data analysis (EDA) to model training, evaluation, and deployment using a Flask web application. --- ## Tech Stack - Python - Pandas, NumPy - Scikit-learn - Matplotlib, Seaborn - Flask - HTML (Jinja2 Templates) --- ## Project Structure ``` end to end ML PROJ/ │ ├── application.py ├── models/ │ ├── ridge.pkl │ └── scaler.pkl ├── notebooks/ ├── templates/ │ └── index.html ├── requirements.txt └── README.md ``` --- ## How to Run the Project ### Step 1: Clone the repository ``` git clone github.com cd REPO_NAME ``` ### Step 2: Create a virtual environment ``` python -m venv venv source venv/bin/activate # macOS/Linux venv\Scripts\activate # Windows ``` ### Step 3: Install dependencies ``` pip install -r requirements.txt ``` ### Step 4: Run the Flask application ``` python application.py ``` Open the browser and visit: ``` 127.0.0.1 ``` --- ## Input Features - Temperature - Relative Humidity (RH) - Wind Speed (Ws) - Rain - FFMC - DMC - ISI - Classes - Region --- ## Output The application predicts the **Fire Weather Index (FWI)** based on the input values. --- ## Note This project is created for learning and academic purposes as part of a Machine Learning / Data Science curriculum. ``` ---