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AsteriaStar
Data-engineering workflow

Training Datasets

The labelled examples a model learns from. Their size, coverage, and biases largely determine how well a model works and where it fails — a classifier only knows the kinds of object it was shown, and inherits any selection effects in how those examples were gathered.

Used across astro-ML

Knowledge connections

Sources

The primary and reference sources this topic draws on.

  • NASANational Aeronautics and Space Administration

    Mission data, planetary science, space telescopes, and public-domain imagery.

    Most NASA-produced imagery is in the public domain; individual items are checked for usage terms before publication.