Explanation: OCI Logging captures logs from job executions and model deployments, including stdout, stderr, and application -specific logs, which helps in debugging, auditing, and monitoring workflows. What are the typical logs collected during model deployment execution? (Choose two)
Explanation: OCI Logging supports log filtering and search capabilities, enabling quick diagnostics. It also integrates with Monitoring to define alarms triggered by specific patterns in logs. What is the purpose of OCI Data Science Pipelines?
You have been given a collection of digital files required for a business audit. They consist of several different formats that you would like to annotate using Oracle Cloud Infrastructure (OCI) Data Labeling. Which THREE types of files could this tool annotate?
Functions". What do you use the score.py file for?
Explanation: PythonScriptStep is used to execute Python code, while ModelDeploymentStep handles automated deployment of trained models. These steps streamline MLOps automation within pipelines. What is a benefit of versioning pipelines in OCI Data Science?
Explanation: A pipeline_run is a specific execution of a pipeline, including metadata like input values, status, logs, and outputs for that particular run, aiding monitoring and repeatability. How does the use of Pipelines improve MLOps workflows? (Choose two)
