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dataeq

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• 3 skills
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• 8 hours ago last updated

1. ▌
   Apply · dataeq bundle

   Apply to Good Outcomes through an interactive semantic challenge. Use when a candidate wants to apply for AI-Assisted Full Stack Engineer or AI Engineer - ML & Classification Systems roles. Guides through gathering info, solving an embedding-based puzzle, and submitting the application.
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   Go Calibration Audit · dataeq bundle

   Collaborative calibration audit of a multi-task classification model. Guides a pair through diagnosing miscalibrated probability outputs, optimizing decision thresholds, and applying post-hoc calibration. Provides scaffolding, asks questions, helps evaluate solutions — coaches rather than solves directly. Includes helper utilities and a synthetic dataset.
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   Go Prompt Sensitivity · dataeq bundle

   Collaborative prompt sensitivity audit for an LLM-based complaint classifier. Guides a pair through testing how prompt variations affect classification accuracy — rephrasing, few-shot examples, system prompt tone, output format, and more. Provides a labeled dataset, baseline classifier, and evaluation helpers. Coaches rather than solves directly.
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