dillondaudert / UMAP.jl
Uniform Manifold Approximation and Projection (UMAP) implementation in Julia
Why this job: works in the areas we cover, but does not say which job it does
What it does
The fit function takes two arguments, data (either a column-major matrix or a vector of "points", e.g. vectors), n_components (the number of dimensions in the output embedding), and various keyword arguments. Several important ones are:
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 4 months ago
- Stars
- 145
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.3.0
- Released 4 months ago
- Built with
- Julia
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 66% closed
- 11 still open
- Pull requests
- 31 merged
- 10 waiting
- Releases
- 14
- 2 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Julia 100%
Topics
- dimensionality-reduction
- julia
- machine-learning
- topological-data-analysis
- umap
- visualization
Project record
- JobOther AI tools
- StatusListed
- Commits407
- Forks17
- Watching6
- Stars in 28 days0
- CreatedSep 13, 2018
- First seen by usNov 7, 2026
- CheckedNov 8, 2026