AYA-KHOUMARI/Forecasting-and-Identifying-Global-Export-Opportunities-for-Algerian-Exporters

# 🇩🇿 Forecasting and Identifying Global Export Opportunities for Algerian Exporters > An end-to-end machine learning system that identifies, analyzes, and forecasts international export opportunities for Algerian exporters across agriculture, industry, and services sectors. --- ## Project Overview Algeria's export economy is heavily concentrated in hydrocarbons (~92% of total exports in 2023). This project addresses the strategic need for export diversification by building a data-driven ML system that: - Analyzes global trade flows by product, country, and sector - Identifies untapped international markets for Algerian exporters - Discovers high-demand products Algeria could potentially export - Forecasts future trade volume and value trends The system supports institutions such as **CACI** (Algerian Chamber of Commerce and Industry) and the **Ministry of External Commerce** in strategic planning. --- ## Objectives - Collect and integrate trade data from multiple sources (UN Comtrade, WTO, Trade Map, World Bank) - Engineer meaningful economic features (growth rates, market share, demand indicators) - Apply **clustering** to group countries, products, and sectors by trade patterns - Build **classification** models to detect high-opportunity export markets - Develop **forecasting** models to predict trade trends by product and country - Deploy an interactive **visualization dashboard** for exporters and policymakers --- ## Project Structure ``` algerian-export-opportunities/ ├── data/ │ ├── raw/ # Raw data from UN Comtrade, WTO, etc. │ ├── processed/ # Cleaned, merged, and encoded data │ └── README.md # Dataset sources and description ├── notebooks/ │ ├── 01_data_collection.ipynb │ ├── 02_data_preparation_eda.ipynb │ ├── 03_clustering.ipynb │ ├── 04_classification.ipynb │ └── 05_forecasting.ipynb ├── src/ │ ├── data_loader.py # Multi-source data ingestion │ ├── fe …