Explanation: The Model Deployment service in OCI Data Science provisions compute resources and exposes endpoints for serving cataloged models. It manages autoscaling and deployment infrastructure. What must be done before deploying a model in OCI Data Science? (Choose two)
D. Converts models to GPU -compatible formats Explanation: Autoscaling allows deployed models to automatically adjust resource allocation based on demand. This optimizes cost and performance by scaling up under heavy load and down when idle. How does the ADS SDK support invoking a deployed model programmatically? (Choose two)
What does OCI Generative AI provide as part of its integration with Data Science?
Which are valid types of Operators in OCI Data Science pipelines? (Choose two)
Which service does AI Quick Actions leverage for tasks such as translation and summarization?
Which OCI Data Science feature supports the full LLM lifecycle integration including prompt engineering and inference?
