Karan Rajubhai Sheladiya completed Energy and Renewable: Machine Learning for the Power Grid

Built a leakage-aware gas-turbine TEY predictor using the correct 8 ambient and turbine sensor features, explicitly excluding downstream CO/NOX emissions. Compared a LinearRegression baseline with a tuned RandomForest on a held-out later-year test split, reported MAE/RMSE/R2 honestly, and documented limitations, drift risks, and monitoring guidance in a concise model card.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Model Comparison and Tuning
• Plain-Language Model Communication