Hassan Abdullah 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, and validated on a locked later-period test split. Compared a LinearRegression baseline with a tuned RandomForest, then reported held-out MAE, RMSE, R2, and residual behavior to show the model’s real performance and limits.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Baseline-to-Ensemble Comparison
• Residual Pattern Reading