Arya Pawar 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 holdout split, and honest held-out evaluation. Compared a LinearRegression baseline with a tuned RandomForest, reported MAE/RMSE/R² on unseen later-year data, and documented the model’s intended use, limits, and monitoring plan in a concise model card.

• Leakage-Free Feature Selection
• Honest Time-Based Validation
• Residual Diagnostics
• Practical Model Monitoring