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