implement

Create an implementation based on a plan.

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Repository: pymc-labs/pymc-marketing
Last source activity: March 2, 2026 at 12:43
Detected SKILL.md language: English
Stars: 1,266
Forks: 418

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name: implement
description: Create an implementation based on a plan.
disable-model-invocation: true

# Create an implementation Based on a plan make an implementation: - You must add follow the plan, and read research if you have questions. - Make a test for every section in your implementation using pytest.

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mmm-modeling

Media Mix Modeling with PyMC-Marketing. Use when building MMMs, specifying adstock/saturation transformations, setting priors, fitting multidimensional (geo-level) models, computing channel contributions, ROAS, running budget optimization, calibrating with lift tests, or performing sensitivity analysis. Covers the MMM class, GeometricAdstock, LogisticSaturation, BudgetOptimizerWrapper, and ArviZ diagnostics for marketing models.

2026-09-12

work-in-repo

Learn how to work in the current folder (repository)

2026-07-28

working-with-notebooks

Fixing and validating Jupyter notebooks in pymc-marketing. Use when notebooks fail CI, need arviz_plots 2.x migration fixes, or when source code changes require notebook output updates.

2026-07-28

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implement

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