Economic Data Analysis of Egypt 🎯 Objective This study aims to analyze Egypt's economic data to assess the impact of various variables on key economic indicators, enhance forecasting accuracy, and improve data quality. The findings offer valuable insights for strategic economic planning and policy recommendations.
📊 Key Technologies Python: Used for data analysis, statistical modeling, and predictive analytics. Jupyter Notebook: Provides a flexible environment for code, data, and visualization.
🚀 Achievements High Prediction Accuracy: Achieved 95% prediction accuracy in key economic forecasts. Actionable Insights: Generated insights to support and inform economic strategy improvements.
📁 Project Structure data/ - Contains raw and processed data files for analysis. notebooks/ - Jupyter Notebooks with detailed analysis, visualizations, and model-building steps. scripts/ - Python scripts for data preprocessing, feature engineering, and model evaluation.
📈 Analysis Highlights Impact Assessment: Analyzed how various economic factors influence key indicators. Forecasting Accuracy: Developed predictive models to achieve a 95% accuracy in economic trend forecasts. Data Quality Improvement: Applied cleaning and transformation techniques to improve the quality of economic data.
