WiMLDS Paris — Workshop on Bayesian Workflows with CmdStanPy
On the 10th of September 2019, the WiMLDS Paris team got the pleasure to host its very first coding workshop at Agorize and welcomed Mitzi Morris. Mitzi Morris is a member of the Stan development team and the developer of CmdStanPy.
Mitzi has worked as a software engineer in both academia and industry. She started out writing tools for Natural Language Processing in C and Java, then moved to genomics and biomedical informatics where she built pipelines for high-throughput sequencing electronic medical records data, all of which led to an increased interest in doing more and better statistics. She has been a Stan contributor since 2014 and joined the Stan team at Columbia in 2017.
The point of the workshop was to learn how to implement Bayesian workflows using CmdStanPy (a Python interface for Stan). During the workshop, we worked with a very fun dataset and made predictions using Bayesian methods.
CmdStanPy allows pythonistas to add the power of Bayesian inference to their toolkit via a small set of functions and objects designed to use minimal memory and parallelize computation.
Given a dataset and a statistical model written as a Stan program, CmdStanPy compiles the model, runs Stan’s MCMC sampler (via CmdStan) to obtain a sample from the posterior, and assembles this sample as a numpy nd-array or pandas.dataframe for downstream visualization and analysis.
👩💻 We had a lovely evening with Mitzi and hope to organize more events similar to this one in the future. If you want to join our meetups, join our page.
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