probabilistic matrix factorization

OriolAbril commented 3 years ago

File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/case_studies/probabilistic_matrix_factorization.ipynb Reviewers: @colcarroll

Known changes needed

Changes listed in this section should all be done at some point in order to get this notebook to a "Best Practices" state. However, these are probably not enough! Make sure to thoroughly review the notebook and search for other updates.

General updates

Use numpy Generator. See also https://numpy.org/doc/stable/reference/random/index.html?highlight=random%20sampling%20numpy%20random#quick-start

Changes for discussion

Changes listed in this section are up for discussion, these are ideas on how to improve the notebook but may not have a clear implementation, or fix some know issue only partially.

ArviZ related

Use ArviZ and xarray for postprocessing. This will probably be challenging. I'd recommend familiarizing with xarray before working on that. Some ideas:
- _norms in code cell 23 looks like it could be replaced by xr.apply_ufunc (using input_core_dims)
  Notes

Exotic dependencies

None

Computing requirements

Model samples in roughly 1 hour

OriolAbril commented 3 years ago

Note: the "good first issue" label only applies to updating the notebook from To Do to General Updates.

chiral-carbon commented 3 years ago

Hi @OriolAbril , can I take this issue up? I am going through the probabilistic matrix factorization notebook at the moment and thought I could attempt to make the recommended changes.

OriolAbril commented 3 years ago

Definitely, I'll assign it to you. Let me know if you have any doubts, especially on xarray which can be challenging even for seasoned pymc3 users

chiral-carbon commented 3 years ago

sure, thanks! I'll get back to you on this.

percevalve commented 2 years ago

Looking into this one.

pymc-devs / pymc-examples