pymc-labs/pymc-marketing
Mar 2026 – Apr 2026
2 Months active
Languages Used
PythonJavaScript
Technical Skills
Jupyter NotebookPythondata analysisdata visualizationmachine learningLaTeX
Tim McWilliams
PROFILE
Tim Mcwilliams
Contributed to pymc-labs/pymc-marketing by developing comprehensive documentation and visualization utilities for adstock transformations, enabling end-to-end analysis workflows in Jupyter Notebooks. Leveraged Python, Plotly, and Sphinx to implement an adstock_timeseries helper, interactive visualizations, and retina-optimized figures, supporting marketing analysts with practical guidance and onboarding resources. Enhanced the Adstock guide’s mathematical clarity by improving LaTeX rendering and ensuring compatibility with MathJax 3 and 4, while resolving integration issues with Plotly and stabilizing the documentation build process. The work focused on reliability, clarity, and usability, resulting in clearer, math-rich documentation and streamlined workflows for practitioners.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
2,868
Activity Months2
Your Network
18 peopleWork History
April 2026
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for pymc-labs/pymc-marketing. Focused on delivering a robust LaTeX rendering enhancement in the Adstock guide, improving math notation fidelity and doc reliability. Implemented MathJax 3/4 compatible configuration, resolved Plotly integration quirks, updated dependencies, and stabilized the documentation build process. Result: clearer math-rich docs, fewer rendering issues, and a smoother authoring experience for marketing materials.
1 Commits • 1 Features
Apr 1, 2026April 2026 monthly summary for pymc-labs/pymc-marketing. Focused on delivering a robust LaTeX rendering enhancement in the Adstock guide, improving math notation fidelity and doc reliability. Implemented MathJax 3/4 compatible configuration, resolved Plotly integration quirks, updated dependencies, and stabilized the documentation build process. Result: clearer math-rich docs, fewer rendering issues, and a smoother authoring experience for marketing materials.
April 2026
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered Adstock Transformations Documentation and Visualization Utilities for PyMC-Marketing in pymc-labs/pymc-marketing. Implemented a new adstock_timeseries helper, interactive Plotly visualizations, and retina-optimized figures; created a comprehensive guide, gallery visuals, and best-practice notes on prior sampling and decay plots. The work enables end-to-end notebook workflows with a single-plot comparison of all adstock transformations, accelerating user onboarding and decision support. Co-authored with Juan Orduz; commit 4518dfcb67055a7168a62ce0825581574dadf065. This enhances modeling reliability, reduces time-to-value for marketing analysts, and strengthens documentation-driven adoption.
March 2026
1 Commits • 1 Features
Mar 1, 2026March 2026: Delivered Adstock Transformations Documentation and Visualization Utilities for PyMC-Marketing in pymc-labs/pymc-marketing. Implemented a new adstock_timeseries helper, interactive Plotly visualizations, and retina-optimized figures; created a comprehensive guide, gallery visuals, and best-practice notes on prior sampling and decay plots. The work enables end-to-end notebook workflows with a single-plot comparison of all adstock transformations, accelerating user onboarding and decision support. Co-authored with Juan Orduz; commit 4518dfcb67055a7168a62ce0825581574dadf065. This enhances modeling reliability, reduces time-to-value for marketing analysts, and strengthens documentation-driven adoption.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
JavaScriptPython
Technical Skills
Jupyter NotebookLaTeXMathJaxPlotlyPythonSphinxdata analysisdata visualizationdocumentationmachine learning
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