pymc-devs / pymc-devs/pymc-examples
GP marginal
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 398
- Forks
- 325
- Avg merge
- 9d 15m
- Merged PRs (30d)
- 1
Description
File: https://github.com/pymc-devs/pymc-examples/blob/main/examples/gaussian_processes/GP-Marginal.ipynb
Reviewers: @bwengals
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
- Typo reported in https://github.com/pymc-devs/pymc3/issues/4587
- use numpy Generator, see also https://numpy.org/doc/stable/reference/random/#quick-start
ArviZ related
- ?
Notes
Exotic dependencies
None
Computing requirements
A couple models seem to take ~20 mins to run.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Open GP-Marginal.ipynb and review the notebook end to end before making changes. Check the reported typo, update random-number usage to NumPy Generator, and review the ArviZ-related content and other outdated material. Run the notebook, including the models that may take about 20 minutes, and finish when the notebook is in a Best Practices state.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, numpy, python
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100