An end-to-end machine learning system that predicts atmospheric visibility from weather parameters such as dry bulb temperature, relative humidity, wind speed, wind direction, and sea level pressure. Built with FastAPI, Scikit-learn, XGBoost, Docker, and GitHub Actions following MLOps best practices.
github python docker weather data-science machine-learning climate scikit-learn regression meteorology xgboost mlops github-actions fastapi github-config visibility-prediction
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Updated
Aug 11, 2026 - Python