Hrithik Tiwari completed Energy and Renewable: Machine Learning for the Power Grid

Built an end-to-end turbine yield predictor using leakage-free sensor inputs, a time-based train/test split, and honest held-out evaluation. Compared a LinearRegression baseline with a tuned RandomForest, improved MAE from 2.90 to 1.53 MWh on the held-out period, and documented the model’s intended use, limits, and monitoring plan in a concise model card.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Model Card Risk Communication