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8/23/2024
README.md

UMAP Dimensionality Reduction API

This is a high-performance dimensionality reduction microservice using UMAP (Uniform Manifold Approximation and Projection). It provides an efficient way to reduce high-dimensional data to 2D or 3D representations, making it easier to visualize and analyze complex datasets.

When to Use This Service

  • Visualizing high-dimensional data in 2D or 3D space
  • Reducing dimensionality of large datasets for machine learning tasks
  • Exploring relationships and clusters in complex data
  • Preprocessing step for other machine learning algorithms

Common Use Cases

  • Visualizing word embeddings in a scatterplotcs
  • Exploring customer segmentation in marketing analytics
  • Visualizing image embeddings in computer vision tasks
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