adool284/Egypt-Population-GDP-and-Unemployment-

An interactive Machine Learning web app to simulate and predict Egypt's future GDP, population, and unemployment. Built with Python & Streamlit. Egypt Economic and Demographic Simulator Project Overview The Egypt Economic and Demographic Simulator is an interactive, machine learning-powered web application designed to predict the future of Egypt's key demographic and economic indicators. By leveraging historical data, the simulator allows users to explore future trends and conduct dynamic "What-If" scenarios to understand the complex relationship between population growth, economic output (GDP), and unemployment rates. Key Features Future Prediction: Utilizes a trained Linear Regression model to forecast Population, GDP, and Unemployment up to the year 2050. What-If Analysis (Simulation): Allows users to manually adjust Population and GDP growth modifiers to instantly visualize their simulated impact on the unemployment rate. Visual Comparison Dashboard: Features an interactive dashboard to select and compare data between any two years using clear, side-by-side bar charts. Interactive User Interface: Includes a mouse-responsive parallax background and an integrated audio player for an immersive user experience. Technologies and Tools Programming Language: Python Machine Learning: Scikit-Learn (Linear Regression), Joblib Data Manipulation: Pandas Web Framework: Streamlit Data Source: Historical datasets sourced directly from the World Bank. Project Context This project was developed as part of the Digital Egypt Pioneers Initiative (DEPI) - Machine Learning Engineer Track, applying practical concepts of data preprocessing, statistical modeling, and interactive deployment. Author Adel Mohamed Abdelreheem Emam Data Science and Statistics Student, Damanhour University