Bayesian techniques present a compelling alternative to the frequentist view of statistics, providing a flexible approach to extracting a swathe of meaningful information from your data. The learning curve is somewhat steep, but the benefits of adding Bayesian techniques to your tool suite are enormous!
What are the bare essentials that you need to know to start applying Bayesian techniques? This talk will provide an entry level discussion covering the following topics:
- What can Bayes do for me? (A brief introduction to Bayesian methods)
- Understanding Markov Chain Monte Carlo. (MCMC is what happens behind the scenes)
- What is Stan? (Writing models in Stan)
- Using Stan in Python. (The PyStan package)
The talk will be peppered with useful tips for dealing with the initial challenges of using Stan with Python.