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Bayesian data science

Thursday, September 8, 2016 - 16:00
Alexandre Bouchard-Côté, Associate Professor, UBC Statistics
Seminar
Room 4192, Earth Sciences Building, 2207 Main Mall

Speaker's Page

Two arguments for not using Bayesian statistics in a data science context are:

1. Having to wait for several hours of MCMC simulation every time you fix a bug in your model.

2. Worse: having to spend several months implementing finicky MCMC algorithms.

I will talk about the work of my collaborators, students, and myself on trying to make this suffering less severe, using ideas from the disparate fields of statistical mechanics and software engineering.

**Warning:** This will mostly be an unconventional talk: a large chunk will be devoted to introducing "blang", an experimental probabilistic programming language for Bayesian data science we are working on.  **Please bring your laptop with Chrome installed.**

Please also let me know (bouchard [at] stat.ubc.ca) if you are interested in staying after the talk for continuing with pizza and a more hands-on primer to declarative Bayesian data science with blang.