Which of these options allow the sharing and loading back of ML models into a...

Detailed Answer in Step-by-Step Solution:

Objective: Identify the mechanism for sharing and reloading ML models in OCI Data Science.

Evaluate Options:

A. Model provenance: Tracks model origin—informative but not a sharing mechanism.

B. Model taxonomy: Categorizes models (e.g., regression)—not for sharing/loading.

C. Model deployment: Makes models accessible as endpoints, not for notebook reloading.

D. Model catalog: Stores models and artifacts, enabling sharing and loading into sessions.

Reasoning: The Model Catalog is OCI’s centralized repository for saving, sharing, and retrieving models (e.g., via ADS SDK).

Conclusion: D is the correct tool.

The OCI Model Catalog “enables data scientists to save trained models and their artifacts, share them with team members, and load them back into notebook sessions for further use or evaluation.” Provenance (A) and taxonomy (B) are metadata, while deployment (C) serves inference, not notebook access. D is explicitly designed for this purpose.

Oracle Cloud Infrastructure Data Science Documentation, "Model Catalog Usage".