Marketing Mix Modeling with Google Meridian using Windsor.ai data — setup guide and example code.
-
Updated
Feb 20, 2026 - Python
#
google-meridian
Here are 4 public repositories matching this topic...
Cloud-agnostic Model Context Protocol (MCP) server for Google Meridian & Marketing Mix Modeling (MMM). Grounded in first principles, data science control points, Bayesian prior calibration, and workflow diagnostics.
python data-science mcp causal-inference bayesian-statistics mmm marketing-mix-modeling cloud-agnostic model-context-protocol fastmcp google-meridian
-
Updated
Aug 1, 2026 - Python
Bayesian Commercial Decision Engine: Google Meridian MMM, SHAP explainability, BG/NBD Customer Lifetime Value, and distributed Apache Spark churn pipelines.
-
Updated
Sep 24, 2026 - Jupyter Notebook
Personal study repository for Google Meridian, an open-source Bayesian Marketing Mix Model (MMM) by Google. Includes notebooks for end-to-end modeling, budget optimization and interactive scenario planning.
-
Updated
Apr 1, 2026 - Jupyter Notebook
Add this topic to your repo
To associate your repository with the google-meridian topic, visit your repo's landing page and select "manage topics."