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ML-forecasting/docs/architecture.mmd
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

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flowchart LR
A[Synthetic monthly demand] --> B[Prepare dates and features]
B --> C[Trimmed-mean baseline]
B --> D[Gradient-boosting model]
C --> E[Rolling validation]
D --> E
E --> F[Select by sMAPE]
F --> G[12-month forecast]
H[Manual trigger today] -.-> B
I[Future Airflow boundary] -.-> B
subgraph Delivery["Delivery ownership"]
J[Business question] --> K[Reproducible evidence]
K --> L[Review and adoption]
end