TFP Tutorial

I have added two tutorial videos on using TFP for inference, focusing on:

I. Specifying graphical models either by

1. manually specifying a joint distribution
2.  using the JointDistributionXXX TFP classes

II. Performing MAP inference

III. Performing MCMC inference.

I do not go into the theory, but the basic idea of MAP and MCMC inference is explained, as well as how you specify what to condition on. 

The notebooks are here:

https://github.com/olethrosdc/ml-society-science/blob/master/src/bayesian-inference/TFP-Tutorial.ipynb

https://github.com/olethrosdc/ml-society-science/blob/master/src/bayesian-inference/JointNamedExample.ipynb

TFP is a bit finicky, so sometimes you get weird errors even if you try and something simple.