QuantEcon / QuantEcon/lecture-python-intro
[linear_equations] Linea Algebra Lecture improvements
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enhancement
reading-group-2024
- Dominant language
- Jupyter Notebook
- Stars
- 65
- Forks
- 32
- Avg merge
- 4d 14h
- Merged PRs (30d)
- 6
Description
This issue will collect comments from the Feb 2024 reading group meeting on
https://intro.quantecon.org/linear_equations.html
Many thanks @SylviaZhaooo and @longye-tian for suggestions.
- Give an overview that states the aim of the lecture -- to learn how to solve large systems of linear equations, and add a link to https://intro.quantecon.org/linear_equations.html#more-goods
- Add a link to
numpylecture. - Potentially break the lecture into two -- one on concepts and one on computation.
- Potentially add a lecture on matrix calculus (perhaps using
sympymatrix calculus?)
Contributor guide
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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 with the linked linear equations lecture and review each checklist item, including the overview, NumPy link, possible lecture split, and possible SymPy matrix-calculus lecture. Before editing, clarify which optional proposals are in scope; done means the agreed lecture improvements are documented and the resulting content links and structure are reviewed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, numpy, python
- Domain
- content, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100