This is the twentieth lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig, updated for the Summer Term 2021 at the University of Tübingen.
Slides available at https://uni-tuebingen.de/en/180804.
Contents:
* How to design probabilistic machine learning solutions
* Latent Dirichlet Allocation
* conditional independence (rejoinder)
* Gibbs sampling (rejoinder)
© Philipp Hennig / University of Tübingen, 2021 CC BY-NC-SA 3.0
