Dharm Dobariya completed Energy and Renewable: Machine Learning for the Power Grid

Built an end-to-end gas-turbine TEY predictor using leakage-free sensor inputs and a genuine time-based holdout. Compared a LinearRegression baseline against a tuned RandomForest, evaluated on held-out MAE/RMSE/R², and documented the model’s intended use, limits, and monitoring plan in a concise model card.

• Leakage-Free Feature Selection
• Time-Based Model Validation
• Honest Held-Out Evaluation
• Plain-Language Model Communication