Model Registry
2024 | AI Dictionary
What is Model Registry: A system that helps track and manage machine learning models throughout their lifecycle, storing versions and deployment status.
What is Model Registry?
A model registry is a system that helps track and manage machine learning models throughout their lifecycle. It stores information about different versions of models, their metadata, performance metrics, and deployment statuses, allowing teams to manage and deploy models in an organized manner.
Benefits of Model Registry
- Version Control : Keeps track of different versions of models, ensuring consistency and reproducibility.
- Model Discovery: Facilitates easy access to models with the ability to search and categorize based on various attributes.
- Collaboration: Enables teams to collaborate by providing a central repository for model artifacts and metadata.
- Deployment: Supports seamless deployment and monitoring of models in production.
Example of Model Registry
In a machine learning project using MLflow :
- Model Storage: The trained models are saved in the registry.
- Versioning: Each model version is tagged with version numbers and metadata.
- Model Promotion: The model can be moved through stages (e.g., from staging to production) for deployment.
This allows for efficient model management and traceability.
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