A carbon-aware ML training scheduling system that optimises machine learning workloads using real-time UK grid carbon intensity data. It simulates ML training, finds optimal low-carbon execution windows, and visualises carbon savings through an interactive multi-page Streamlit analytics dashboard.
python machine-learning reinforcement-learning scheduling q-learning ieee green-ai net-zero carbon-aware uk-grid
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Updated
Jun 24, 2026 - Python