From the course: MLOps Essentials: Model Development and Integration

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Model registry

Model registry

From the course: MLOps Essentials: Model Development and Integration

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Model registry

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- [Instructor] Similar to how data is cataloged in feature stores and code is stored in code repositories, models do need their own registry to manage their life cycle. A model registry is a repository for storing and tracking machine learning models. It is a database that contains the model and metadata about the model. The database can be queried at any time to access the model and information about it. It is constantly updated with all status changes and associated audit trails. What information is captured in the model registry about the model? First, a serialized version of the model, like a pickle file is stored in the registry, Metadata about the model, including a unique model ID, version, and description of the model is stored. Hyper parameters used for the model is a key metadata to capture. Then there is model status based on which stage of the life cycle the model is currently in. There is also an audit…

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