python-analytics-skills
Bayesian modeling, model evaluation, and reactive Python notebooks
All Skills in This Repository (5)
Pure Emerald Level Indicators
pymc-labsmodel-evaluation
Compare Bayesian models with ArviZ 1.1 LOO, ELPD, and Bayes factors.
pymc-labsprior-elicitation
Find constrained priors for Bayesian models using PyMC and PreliZ.
pymc-labspymc-testing
Mock PyMC model sampling and provide pytest fixtures for testing.
pymc-labsmarimo-notebook
Run Python notebooks with reactive cell execution on dependencies.
pymc-labspymc-extras
Add B-spline basis functions and distributional regression to PyMC models.
Frequently Asked Questions
FAQPage SchemaHow to install python-analytics-skills?▼
Run `npx skills add pymc-labs/python-analytics-skills --all -g -y` in your terminal to install all skills globally.
What does this skill suite do for Bayesian modeling?▼
It gives your coding assistant expert knowledge for building PyMC models, choosing priors, running MCMC, checking convergence, and comparing models with LOO-CV.
How do I speed up PyMC model testing?▼
The pymc-testing skill teaches mock sampling patterns that replace slow MCMC runs with fast prior predictive checks, ideal for CI pipelines.
Does it work with Claude Code and Cursor?▼
Yes. All skills follow the universal SKILL.md standard and load automatically in Claude Code, Cursor, Gemini CLI, and other compatible platforms.
Can it help build reactive Python notebooks?▼
Yes. The marimo-notebook skill covers reactive cells, UI widgets, SQL queries, caching, and converting Jupyter notebooks to marimo.
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