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What Namratha demonstrated

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 evaluated on a locked-away later-year test split. The final model achieved 1.50 MWh MAE, 1.908 RMSE, and 0.9838 R² on held-out data, with a model card that clearly states limits, drift risks, and monitoring triggers.

  • Leakage-Free Feature Selection
  • Honest Held-Out Evaluation
  • Model Risk Communication

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