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What Swapnil demonstrated

Built and verified a full legacy-code modernization for a fleet maintenance service: fixed the wear calculation so nearly-due cars are flagged, handled missing service readings safely, corrected the nightly report’s average and crash path, and repaired a hidden mileage-conversion bug in shared helpers. Also added a data-driven breakdown-risk analysis that prioritizes active usage signals over total mileage, and documented the review process in NOTES.md.

  • Leakage-Free Feature Engineering
  • Honest Model Evaluation
  • Directed AI Code Review
  • Acceptance-Driven Verification

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