Joginder Singh 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 a LinearRegression baseline and a RandomForest model, and validated on a genuine time-based holdout. The final model was evaluated honestly with MAE, RMSE, R², and residual analysis, and the accompanying model card documented intended use, limits, and monitoring triggers in plain language.

• Leakage-Free Feature Selection
• Time-Based Holdout Validation
• Honest Held-Out Evaluation
• Plain-Language Model Communication