Ashish completed Energy and Renewable: Machine Learning for the Power Grid

Built a leakage-aware turbine yield predictor end to end: framed TEY as a regression target, used the eight legitimate ambient/turbine sensors while excluding downstream CO/NOX emissions, and validated on a locked later-period test split. Compared a LinearRegression baseline with a RandomForest, then reported honest held-out MAE, RMSE, and R² alongside a residual read and a concise model card for operational use.

• Leakage-Free Feature Selection
• Time-Based Holdout Evaluation
• Baseline-to-Ensemble Comparison
• Plain-Language Model Communication