Calling all Bayesian enthusiasts and PyMC aficionados! Join us for an exciting hackathon this coming Monday focused on implementing statistical models from the posteriordb repository with the current version of PyMC.
posteriordb is a comprehensive library of Bayesian statistical models, data sets, and reference posterior inferences. It is designed to facilitate the testing and evaluation of inference algorithms across a wide range of models, enabling assessments of accuracy, speed, and scalability. It is a valuable resource for students and instructors, offering easy access to a diverse collection of pedagogical and real-world examples with detailed model definitions, well-curated data sets, and reference posterior samples. The library is framework-agnostic and can be accessed seamlessly from both R and Python, making it a versatile tool for researchers, developers, and educators in the field of Bayesian statistics and probabilistic programming.
What: A collaborative coding event to enhance PyMC’s presence in posteriordb
When: Monday, August 12, 14:00 UTC (10:00 Eastern)
Where: PyMC Discord(https://discord.gg/rTUYbwc9fe) hackathon voice channel: https://discord.com/events/974333176623280130/1270570787505573899
Highlights:
- Work on real-world statistical models from diverse fields
- Contribute to the PyMC ecosystem
- Collaborate with fellow Bayesian practitioners
- Learn from experienced PyMC developers
We’ll be writing models from posteriordb, a database of posterior distributions for various Bayesian inference problems. This is your chance to enhance contribute to the project by making these models available to the wider probabilistic programming community.