I like how pyro from Uber is structured, that it uses pytorch and how many features it brings. Pymc looks ok as well (but would not be my favorite with regards to the syntax and lifetime!)
Do you have a book you would highlight for learning probabilistic programming, the variational inference, ...
I found books using pymc
- https://github.com/BayesianModelingandComputationInPython/BookCode_Edition1 and
And the book "Variational Methods for Machine Learning with Applications to Deep Networks" with ~140 pages seems rather short (and the table of contents did not convince me yet).
Do you have suggestions. Should I just go with one of the pymc books? (Although pymc3 will die sooner or later because it is based on theano, which is deprecated - I would prefer a pytorch or Jax based probabilistic programming language)