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Add privacy-safe demand forecasting case study

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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
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<title id="title">Demand forecasting delivery architecture</title>
<desc id="desc">Synthetic demand flows through preparation, baseline and model, rolling validation, selection, and a twelve-month forecast. Manual triggering today has a future Airflow boundary.</desc>
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<text class="text" x="302" y="185">Prepare</text><text class="text" x="302" y="208">features</text>
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