This is a series of lecture notes for probabilistic topic models written in ipython notebook.
The following metarials will be covered:
- Dirichlet distribution
- Latent Dirichlet allocation (LDA)
- Gibbs sampling
- Variational inference
- Dirichlet process
- Hiearchical Dirichlet process (HDP)
See lectures on nbviewer.com