Md Riazul Arefin

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Md Riazul Arefin

Mechanical Engineering · National Institute of Technology Tiruchirappalli

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Projects

Certified

Self-directed project

Energy and Renewable: Machine Learning for the Power Grid

Junior Machine Learning Engineer · AI / ML · September 2026

92/ 100

A ProoV case study · educational project, not employment

Built an end-to-end turbine yield predictor using leakage-free sensor inputs and a genuine time-based holdout. Compared a LinearRegression baseline with a tuned RandomForest, evaluated on held-out MAE/RMSE/R2, and documented the model’s intended use, limits, and drift-monitoring plan in a concise model card.

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
  • Correctly excluded CO and NOx as downstream leakage features and explained why they were not available at prediction time.
  • Used a genuine time-based split instead of a random shuffle, with the later period locked away for testing.
  • Compared a LinearRegression baseline against a RandomForest and showed a clear held-out improvement in MAE and R2.
  • Included a residual read and a monitoring plan that focuses on input-range drift and rising rolling error.
  • Leakage-Free Feature Selection
  • Honest Held-Out Evaluation
The work I submitted20 tasks

12 tasks · 13 lines · Python, JavaScript · 8 written answers · 434 words

  • Problem Frame169 characters
  • Leakage Flags113 characters
  • Train Validate BaselinePython · 1.4k characters
  • Train Validate Forest944 characters
  • Train Validate124 characters
  • Tune Evaluate SetupPython · 1.5k characters
  • Tune Evaluate ResidualsPython · 2 lines
  • Tune Evaluate132 characters
  • Residual Read413 characters
  • Drift Monitor93 characters
  • Model Card1.2k characters
  • Teach BackJavaScript · 768 characters
  • Problem Frame11 words
  • Leakage Flags1 word
  • Train Validate Baseline141 words
  • Train Validate Forest77 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.

Verified certificateTamper-proof · issued by ProoV
1Project completed
1Verified certificate
92Average score
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