[ANN] UMAP.jl, a pure Julia implementation of Uniform Manifold Approximation and Projection

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UMAP.jl is a pure Julia implementation of the UMAP dimension reduction algorithm. From the abstract:

UMAP (Uniform Manifold Approximation and Projection) is a novel manifold learning technique for dimension reduction. UMAP is constructed from a theoretical framework based in Riemannian geometry and algebraic topology. The result is a practical scalable algorithm that applies to real world data.

The first release, v0.1.0, is tagged in the General registry and can be installed with ]add UMAP. More usage details are available in the README.

Example:

MNIST UMAP.jl
MNIST UMAP.jl749×520 35.9 KB

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Good job !

Did you compare the speed of the algorithm between the python implementation of the original author (with numba speed up) and your version ?

I want to see which version I have to use :slight_smile:

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