Jeevan Merkaji Somanna completed Energy and Renewable: Machine Learning for the Power Grid

Built a turbine energy-yield regressor end to end on the UCI gas-turbine dataset: framed TEY as the target, excluded downstream CO/NOx leakage features, trained a LinearRegression baseline and a tuned RandomForest, and validated on a held-out later time period. Reported honest held-out MAE/RMSE/R² and documented deployment limits, drift risks, and a monitoring threshold in a concise model card.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Residual-Based Error Reading
• Practical Model Documentation