Arunkumar Kesavan completed Energy and Renewable: Machine Learning for the Power Grid
What Arunkumar demonstrated
Built a turbine TEY predictor end to end using leakage-free sensor features, a LinearRegression baseline, and a tuned RandomForest. Evaluated on a locked-away later time period, the model achieved MAE 1.532 MWh, RMSE 1.937 MWh, and R² 0.9833, and the candidate documented the model’s intended use, limits, and monitoring plan in a concise model card.
- Leakage-Free Feature Selection
- Held-Out Model Evaluation
- Residual-Based Error Reading
- Plain-Language Model Communication
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