KUNAL ANANT KHANDAGALE completed Energy and Renewable: Machine Learning for the Power Grid

Built an end-to-end turbine yield predictor using leakage-free sensor inputs and a genuine time-based split. Compared a LinearRegression baseline with a tuned RandomForest, evaluated on held-out data with MAE, RMSE, and R2, and documented the model’s limits, drift risks, and monitoring plan in a concise model card.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Residual Diagnostics
• Plain-Language Model Communication