Correct Answer: A
Detailed Answer in Step-by-Step Solution:
* Objective: Identify which activity isn't part of the ML lifecycle.
* Define ML Lifecycle: Includes data access, preparation, modeling, evaluation, deployment, and monitoring.
* Evaluate Options:
* A: Database Management (e.g., DBA tasks) is IT-related, not specific to ML workflows.
* B: Model Deployment (e.g., serving predictions) is a key ML phase-correctly included.
* C: Modeling (e.g., training) is the core of ML-correctly included.
* D: Data Access (e.g., retrieving data) is the first ML step-correctly included.
* Reasoning: Database management supports infrastructure, not the ML process directly.
* Conclusion: A is the outlier.
The OCI Data Science lifecycle includes "data access, exploration, feature engineering, modeling, deployment, and monitoring," per the documentation. Database Management (A) is a general ITtask (e.g., optimizing Oracle DB), not an ML-specific activity, unlike B, C, and D, which are integral to OCI's ML pipeline.
Oracle Cloud Infrastructure Data Science Documentation, "Machine Learning Lifecycle Overview".
