The Human Development Index (HDI) Predictor is a Machine Learning project that predicts the HDI score of a country using important development indicators such as Life Expectancy, Expected Years of Schooling, Mean Years of Schooling, and Gross National Income (GNI) Per Capita.
The project is built using Python, Scikit-learn, and Flask, allowing users to enter input values through a web interface and receive the predicted HDI score instantly.
- Data preprocessing and cleaning
- Data visualization using Matplotlib and Seaborn
- Linear Regression model for HDI prediction
- Model evaluation using regression metrics
- Flask-based web application
- Simple and user-friendly interface
- Python
- NumPy
- Pandas
- Matplotlib
- Seaborn
- Scikit-learn
- Flask
- HTML
- CSS
HDI_Prediction_Project/
│
├── Dataset/
├── Training/
├── Flask/
├── screenshots/
├── README.md
├── requirements.txt
└── .gitignore
The dataset is based on Human Development indicators published by the United Nations Development Programme (UNDP). It includes:
- Country
- HDI
- Life Expectancy
- Expected Years of Schooling
- Mean Years of Schooling
- GNI Per Capita
- Algorithm: Linear Regression
- R² Score: 0.9760
- Mean Absolute Error: 0.0161
- Mean Squared Error: 0.000485
- Clone the repository.
- Install the required packages.
pip install -r requirements.txt- Run the Flask application.
cd Flask
python app.py- Open your browser and visit:
http://127.0.0.1:5000
Mohammed Sheraj
B.Tech – Computer Science and Engineering (Artificial Intelligence)
This project was developed as part of the Artificial Intelligence & Machine Learning Virtual Internship.