The notebook contains an introduction to Bayesian Statistics using the package PyMC3. It accompanies the talk from the second PyData Athens meetup.

The notebook contains the following case studies:

  1. The biased coin problem
  2. Bayesian Linear Regression
  3. A change-point model for a time series of recorded coal mining disasters
  4. Stochastic Volatility estimation during the 2008 financial crisis
  5. Pareto/NBD Model for Customer Lifetime Value prediction

Useful Resources:

  1. Getting started with PyMC3 (http://docs.pymc.io/notebooks/getting_started)
  2. The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo (D. Hoffman, A. Gelman - 2014)
  3. Bayesian Methods for Hackers (Cameron Davidson-Pilon - https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)
  4. Doing Bayesian Data Analysis (John Kruschke)
  5. Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model (Peter S. Fader, Bruce G. S. Hardie, Ka Lok Lee)