Self-directed project
Energy and Renewable: Machine Learning for the Power Grid
Junior Machine Learning Engineer · AI / ML · July 2026
A ProoV case study · educational project, not employment
Built an end-to-end turbine yield predictor using leakage-free sensor inputs, a time-based held-out split, and honest evaluation. Compared a LinearRegression baseline with a tuned RandomForest, then documented the model’s accuracy, limits, and monitoring plan in a decision-ready model card. The final artifact shows strong judgment around data leakage, validation, and operational deployment risk.
Graded against
- Build and validate the model correctly35%
- Optimize and evaluate honestly25%
- Write the Model Card (clarity + honesty)25%
- Explain it to a non-expert15%
Passed · pass mark 60/100
What stood out6
- Dropped CO and NOx explicitly because they are measured downstream of the prediction moment, avoiding leakage.
- Used an earlier-years train / later-years test split and reported held-out metrics instead of training performance.
- Compared a linear baseline against a RandomForest and showed a clear MAE improvement on the locked test set.
- Interpreted residuals and documented a realistic silent-drift monitoring plan with a retrain threshold.
- Leakage-Free Feature Selection
- Held-Out Evaluation Discipline
The work I submitted20 tasks
12 tasks · 13 lines · Python, JavaScript · 8 written answers · 438 words
- Problem Frame199 characters
- Leakage Flags113 characters
- Train Validate BaselinePython · 1.4k characters
- Train Validate Forest943 characters
- Train Validate124 characters
- Tune Evaluate SetupPython · 1.5k characters
- Tune Evaluate ResidualsPython · 2 lines
- Tune Evaluate129 characters
- Residual Read434 characters
- Drift Monitor95 characters
- Model Card2.4k characters
- Teach BackJavaScript · 1.1k characters
- Problem Frame16 words
- Leakage Flags1 word
- Train Validate Baseline141 words
- Train Validate Forest76 words
- Train Validate1 word
- Tune Evaluate Setup110 words
- Tune Evaluate Residuals92 words
- Tune Evaluate1 word
Summarised on purpose — the submitted code and writing stay private so this page cannot be reused as an answer key. The full submission sits behind the verified certificate.