Terrymanzi/aquaculture-import-export-prediction

a linear regression model predicting African countries' aquaculture import and exports annually. # Aquaculture Trade Prediction System A machine learning-powered App for predicting annual aquaculture import and export volumes for African countries. ## Mission My mission is to empower African fisheries and aquaculture stakeholders with accessible data-driven insights by providing a friendly tool that predicts import and export trade volumes annually. My goal is to simplify decision-making through machine learning while promoting transparency and planning in regional aquaculture trade. ## Live Demo 🎥 **YouTube Demo**: Watch the 5-minute demo 🔗 **Public API**: aquaculture-import-export-p… Test the API using the Swagger UI interface at the link above. ## Project Overview This project implements a complete end-to-end solution for predicting aquaculture trade volumes using: - **Machine Learning**: Linear Regression, Decision Trees, and Random Forest models - **API**: FastAPI backend with data validation and CORS support - **Mobile App**: Flutter application for user-friendly predictions ## Dataset - **Source**: Global Fisheries & Aquaculture Department - **Focus**: African countries' aquaculture trade data - **Commodities**: Fish, Crustaceans - **Time Period**: 2000-2015 (historical data) - **Predictions**: 2000-2050 ## Project Structure ``` linear_regression_model/ │ ├── summative/ │ ├── linear_regression/ │ │ └── multivariate.ipynb # Main ML notebook │ │ │ ├── API/ │ │ ├── prediction.py # FastAPI application │ │ ├── requirements.txt # Python dependencies │ │ ├── best_model.pkl # Saved ML model │ │ ├── scaler.pkl # Feature scaler │ │ ├── country_encoder.pkl # Country label encoder │ │ ├── commodity_encoder.pkl # Commodity label encoder │ │ └── model_metadata.pkl # Model information │ │ │ └── FlutterApp/ │ ├── lib/ │ │ └── main.dart # Flutter application │ └── pubsp …