Jagdish Kalokhe 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 time-based validation split. Compared a LinearRegression baseline against a RandomForest model, reported held-out MAE/RMSE/R2, and documented practical limits, drift monitoring, and intended use in a concise model card.

• Leakage-Free Feature Selection
• Time-Based Holdout Evaluation
• Honest Model Calibration
• Plain-Language Model Communication