gabspereira/ML-forecasting
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Add privacy-safe demand forecasting case study

Browse Source 
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>
This commit is contained in:
Gabriel Pereira
2026-09-11 16:37:33 -03:00
commit 930534dde2
13 changed files with 3624 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

9
docs/publication-checklist.md Normal file
View File

@@ -0,0 +1,9 @@
# 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.