Comet tracks experiments, manages a model registry, and monitors models in production, integrating with the ML frameworks teams already use to log metrics, hyperparameters, and artifacts. It's mostly there to solve the reproducibility problem — being able to actually answer 'which run produced this model and what changed since then' months later.
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