Comet

For data scientists, machine learning engineers, and research teams, Comet helps organize training experiments so they can understand how models change and reproduce useful results. Connect it to an existing workflow to log run details such as parameters, metrics, code, and other assets, then review and compare runs in a shared project dashboard with charts and visualizations. Comet also supports versioning datasets and other artifacts, and managing model versions in a registry linked to their experiments. Teams can use it to investigate model performance, collaborate on experiments, and follow models through development and, with Comet’s production monitoring features, deployment. It is designed for people building and maintaining machine learning models rather than for general-purpose project management.

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