Baynesian Computation, Likelyhood functions. Inference using NUTS or Variational approximation.

The likelihood is a central concept in Bayesian computation. In this tutorial, we will learn about what is the likelihood function and how do we use it for inference. Using PyMC3, I will demonstrate how to get the likelihood from a model, how does it connect to inference using NUTS or Variational approximation, and some practical usage of the model likelihood to perform model comparisons.

Slides: https://github.com/junpenglao/All-that-likelihood-with-PyMC3/tree/pydata_Berlin

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