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What Eisha demonstrated
Built a turbine TEY prediction workflow end to end using leakage-free sensor inputs and a genuine time-based holdout. Compared a LinearRegression baseline with a RandomForest model, showed the forest improved held-out MAE from 2.90 to 1.53 MWh, and documented the model’s limits, including drift outside the observed ambient range.
- Leakage-Free Feature Selection
- Time-Based Model Validation
- Honest Held-Out Evaluation
- Plain-Language Model Communication
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