pymc-marketing

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.

Structure a research based on the user request. Identify what must change in order to complete the task.

Create a plan based on document research through an interactive, iterative process.

Create git commits for changes made during the session.

Learn how to work in the current folder (repository)

Structure a research based on the user request. Identify what must change in order to complete the task.

Create a plan based on document research through an interactive, iterative process.

Create an implementation based on a plan.

Create git commits for changes made during the session.

PyMC-Marketing coding conventions, preferred implementations, and style guidelines.