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laxmi-narayan-87/ml-engineering-suite

v0.1.0

A unified machine-learning engineering toolkit spanning dataset quality, model development, hyperparameter optimization, MLOps pipelines, deployment, monitoring, and rollback.

data-quality-labeling

Use when designing annotation guidelines, auditing training data, sampling examples for labeling, measuring annotator agreement, or preparing versioned ML datasets.

Read SKILL.md at the source

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