EU Regional School - Fonnesbeck Seminar
Prof. Christopher Fonnesbeck, Ph.D. - Probabilistic Programming with Python
Department of Biostatistics, Vanderbilt University Medical Center, USA
Abstract
This intermediate-level course will provide students with hands-on experience applying practical Bayesian statistical modeling methods on real data. PyMC3 is a high-level Python library for building statistical models using probabilistic programming, and fitting them using modern Bayesian computational methods. I will provide an introduction to Bayesian inference and prediction, followed by a tutorial on probabilistic programming with PyMC3, including the use of Markov chain Monte Carlo (MCMC) and Variational Inference (VI), using real-world datasets. The last part of the course will focus on modeling strategies and how to avoid various pitfalls when applying Bayesian statistics to your own work. The course will assume familiarity with Python and with basic statistics (e.g. probability), but does not require previous experience with Bayesian methods or probabilistic programming.