Md. Rakibul Hasan completed Energy and Renewable: Machine Learning for the Power Grid

Built a leakage-aware turbine yield predictor end to end: framed TEY as the target, excluded downstream CO/NOx emissions, trained both a LinearRegression baseline and a RandomForest model, and validated on a locked later-year test split. The candidate reported honest held-out metrics, added a residual read and drift-monitoring plan, and wrote a concise model card explaining intended use, limits, and retraining triggers.

• Leakage-Free Feature Selection
• Honest Held-Out Evaluation
• Baseline-vs-Ensemble Comparison
• Plain-Language Model Communication