Soheib Kadri completed Energy and Renewable: Machine Learning for the Power Grid

Built a leakage-aware turbine yield predictor end to end: framed TEY as a regression target, excluded downstream CO/NOx emissions, trained a LinearRegression baseline and a RandomForest model, and validated on a locked later-period holdout. The final model achieved strong held-out performance and was accompanied by residual analysis plus a model card covering intended use, limitations, and monitoring.

• Leakage-Free Feature Selection
• Time-Based Model Validation
• Honest Residual Analysis