Research ways to speed up brute force cosine similarity
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research
- Dominant language
- Python
- Stars
- 12.5k
- Forks
- 998
- Avg merge
- 3d 13h
- Merged PRs (30d)
- 10
Description
Might be faster to use numpy or some other trick.
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
No file, test, or entry point is named in the issue. Start by locating the brute-force cosine-similarity implementation and measuring its current performance; done means identifying and validating a faster approach, with results recorded for comparison.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- numpy, python
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100