Jongseok Park 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 holdout. Compared a LinearRegression baseline with a tuned RandomForest, then evaluated the final model on unseen later-year data with MAE, RMSE, R², and residual analysis. Also documented intended use, excluded downstream emissions features for a clear reason, and outlined monitoring for drift.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Residual-Based Error Reading
• Practical Model Monitoring