Devanshi completed Energy and Renewable: Machine Learning for the Power Grid

Built a turbine-yield predictor end to end using leakage-free sensor inputs, a LinearRegression baseline, and a tuned RandomForest evaluated on later held-out data. Reported honest held-out performance (about 1.5 MWh MAE, 1.9 RMSE, R²≈0.98), checked residual behavior, and documented the model’s intended use, limits, and monitoring plan in a concise model card.

• Leakage-Free Feature Selection
• Time-Based Holdout Evaluation
• Honest Residual Analysis
• Model Card Communication