Param Pambhar

Create your portfolio with ProoV
ProoV
DE Verified work portfolio

ProoV Portfolio

Param Pambhar

View the ProoV leaderboard

Projects

Certified

Self-directed project

Frontend Engineering with Prediction Game

Junior Front-End Engineer · Software Engineering · July 2026

84/ 100

A ProoV case study · educational project, not employment

Built a complete World Cup prediction game end to end: rendered the fixture board, scored picks with the exact 5/2/0 rules, derived team attack strengths from real results, and used them in a bot predictor that auto-picks every match. Also deployed the finished experience to a live https Netlify URL for immediate sharing.

Graded against

  • Scoring engine correctness30%
  • Prediction model genuinely from real data25%
  • Game completeness and leaderboard soundness25%
  • Shipped and shareable: live deployed URL20%

Passed · pass mark 60/100

What stood out6
  • Implemented the exact scoring rubric, including correct handling of draws and exact-score matches.
  • Computed team strengths from a real-results sample and used those strengths inside the bot prediction logic.
  • Shipped a live Netlify deployment URL that matches the project’s shareable-delivery requirement.
  • Leakage-Free Feature Engineering
  • Honest Model Evaluation
  • End-to-End Game Assembly
The work I submitted18 tasks

10 tasks · 11 lines · JavaScript · 8 written answers · 535 words

  • Lab Orientation647 characters
  • Example Render FixturesJavaScript · 2.2k characters
  • Act1 Fixtures FormJavaScript · 3.6k characters
  • Act2 Scoring FunctionJavaScript · 2.7k characters
  • Example Compute StrengthsJavaScript · 2.0k characters
  • Act3 Compute Strength108 characters
  • Act3 House Bot108 characters
  • Act4 Leaderboard63 characters
  • Act5 Assemble2 lines
  • Final Submission124 characters
  • Lab Orientation56 words
  • Example Render Fixtures111 words
  • Act1 Fixtures Form116 words
  • Act2 Scoring Function99 words
  • Example Compute Strengths150 words
  • Act3 Compute Strength1 word
  • Act3 House Bot1 word
  • Act4 Leaderboard1 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
Certified

Self-directed project

Energy and Renewable: Machine Learning for the Power Grid

Junior Machine Learning Engineer · AI / ML · July 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. Trained and compared a LinearRegression baseline with a RandomForest model, then evaluated the final model on unseen later-period data with MAE, RMSE, R², and residual analysis. Authored a concise model card that explains intended use, excluded downstream emissions features, and the model’s operating limits.

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 outputs and kept only the eight legitimate ambient/turbine sensor features.
  • Used an earlier-years train split and later-years test split, avoiding a random shuffle on time-ordered data.
  • Compared a LinearRegression baseline against a tuned RandomForest and reported MAE, RMSE, and R² on held-out data.
  • Read the residuals and explicitly identified heteroscedasticity as a real limitation.
  • Leakage-Free Feature Selection
  • Honest Held-Out Evaluation
The work I submitted20 tasks

12 tasks · 13 lines · Python, JavaScript · 8 written answers · 363 words

  • Problem Frame112 characters
  • Leakage Flags113 characters
  • Train Validate BaselinePython · 931 characters
  • Train Validate ForestPython · 1.8k characters
  • Train Validate120 characters
  • Tune Evaluate SetupPython · 1.5k characters
  • Tune Evaluate ResidualsPython · 2 lines
  • Tune Evaluate132 characters
  • Residual Read216 characters
  • Drift Monitor91 characters
  • Model Card959 characters
  • Teach BackJavaScript · 817 characters
  • Problem Frame2 words
  • Leakage Flags1 word
  • Train Validate Baseline65 words
  • Train Validate Forest91 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
2Projects completed
2Verified certificates
88Average score
Create your portfolio with ProoV