What is the role of the model catalog in OCI Data Science?

The model catalog in OCI Data Science functions primarily as a repository for storing and managing machine learning models. This centralized location allows data scientists and machine learning practitioners to organize their models systematically, track different versions, and maintain metadata associated with each model.

By storing models in a catalog, teams can facilitate collaboration, enable reproducibility of their work, and ensure easier access to models for shareability and deployment purposes. This centralization is crucial for managing the lifecycle of machine learning projects, from development to production. Overall, a model catalog streamlines the model management process and enhances the overall workflow in data science projects.

While deployment, visualization of performance, and analysis of real-time data streams are essential components of machine learning workflows, they do not define the primary purpose of the model catalog itself.