Documentation: goals, examples, and working with skills
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- Dominant language
- Jupyter Notebook
- Stars
- 8
- Forks
- 4
- Avg merge
- 2d 2h
- Merged PRs (30d)
- 4
Description
ptgp needs documentation. The docs are aimed at human readers, not LLMs. The skills files (#12) are for LLMs.
What ptgp is and what it's for
A landing page that describes the goal of the library, who it's for, and how it's different from other GP libraries.
Examples
Canonical textbook problems and/or real-world examples with interesting datasets. These should be:
- Short and not exhaustive, given the fact that our attention spans have been completely ruined
- Focused on real-world problems where GPs are underused, not just toy regression on a sine wave
- Have attractive, interactive plots
- Don't go into the weeds of every utility and helper
The examples can be pedagogical, but should go beyond "What is a GP?". There are already many good places to learn that and experiment with basic GPs. The examples should be aligned with the goals of ptgp: for practitioners trying to apply GPs to tricky problems.
Ideas
- Decision theory with GP predictive distributions — Rasmussen & Williams Ch. 2.4. GPs give you a full predictive distribution, not just a point estimate. With an asymmetric loss function (e.g. overestimating is much more costly than underestimating), the optimal prediction shifts away from the mean and you need the full distribution to compute it. This comes up constantly in practice (finance, safety, inventory) and is an example I really like. It'd be cool to show how to do this with ptgp on a believable problem and should show off pytensors usefulness too.
Working with skills files
A guide for using ptgp with an LLM via the skills files (see #12). How to install them, what they cover, how to use them to plan and debug a modeling problem interactively.
Open questions
- What would be some cool ideas for docs? What are your favorite existing GP examples?
- What plotting libraries / tools for interactive plots? (Plotly, Bokeh, etc.)
Contributor guide
No contributing guide indexed for this repository
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
Start by reviewing the existing project documentation and issue #12's skills files. Break the work into a landing page, practitioner-focused examples with interactive plots, and a guide for using the skills files with an LLM. It is done when these areas are documented and the open questions about examples and plotting tools are resolved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, plotly, python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 32/100