Files
ML-forecasting/docs/publication-checklist.md
Gabriel Pereira 930534dde2 Add privacy-safe demand forecasting case study
Synthetic monthly SKU/region demand notebook comparing a trimmed-mean
baseline against gradient boosting, with a gated TimesFM build-vs-buy
comparison. Includes rolling-origin validation, executive narrative,
architecture diagram, one-page PDF, and LinkedIn draft.

No company data, credentials, or private implementation details.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-09-11 16:37:33 -03:00

523 B

Publication checklist

  • No credentials, tokens, private keys, .env files, or secret names.
  • No company rows, identifiers, product names, plant names, or business values.
  • No private schemas, endpoints, account names, or internal URLs.
  • All charts and metrics come from synthetic data.
  • Numeric results are labeled illustrative and are not presented as business outcomes.
  • Notebook executes from a clean environment with uv.
  • Diagram and PDF contain only generic architecture terms.