Use Cases

This section is intended to show you what you can do with DagsHub beyond the basics. These guides are intended to make you more efficient and productive while developing and deploying machine learning models.

•  Curate Datasets

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  Create training-ready datasets for ML training with our Data Engine

•  Track ML Experiments

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  Track ML experiments and log them to DagsHub

•  Annotate Datasets

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  Annotate your data from DagsHub

•  Deploy ML Models

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  Deploy ML model from DagsHub to a cloud platform

•  Version Datasets

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  Version data and code as part of an ML project

•  Auto-labeling

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  Use machine learning models to speed up your annotation process

•  Active Learning

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  Create active learning pipelines with our Data Engine

•  Reproduce ML Experiments

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  Reproduce results of ML experiments

•  Data Science Peer Review

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  Conduct peer review as part of a data science project