This project builds a machine learning model to estimate urban household carbon footprints using synthetic data. It analyzes energy use, transport, diet, and lifestyle factors to predict annual CO₂ emissions, offering insights into household sustainability and potential strategies for reducing environmental impact.
☆10Feb 19, 2026Updated 2 weeks ago
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