This repo contains Python notebooks and data to demostrate Bayesian data analysis. The following topics are covered:

• Models

  1. Hierarchical (Multilevel) model
  2. Latent (hidden) probabilistic models: GMM, k-means, etc.

• Inferences:

  1. Sampling based approximate inference
  2. Variation inference
  3. Expectation maximization

The repo also contains notebooks that demonstrate usage of Tensorflow Probability and Pyro.