1z0-1110-23 試験問題を無料オンラインアクセス

You are working as a data scientist for a healthcare company. They decide to analyze the data to find patterns in a large volume of electronic medical records. You are asked to build a PySpark solution to analyze these records in a JupyterLab notebook. What is the order of recommended steps to develop a PySpark application in Oracle Cloud Infrastructure (OCI) Data Science?

• A.Launch a notebook session. Install a PySpark conda environment. Configure core-site.xml.
  Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK.
• B.Launch a notebook session. Configure core-site.xml. Install a PySpark conda environment.
• C.Develop your PySpark application. Create a Data Flow application with the Accelerated Data Science (ADS) SDK.
• D.Configure core-site.xml. Install a PySpark conda environment. Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application. Launch a notebook session.
• E.Install a Spark conda environment. Configure core-site.xml. Launch a notebook session.
  Create a Data Flow application with the Accelerated Data Science (ADS) SDK. Develop your PySpark application.

You want to ensure that all stdout and stderr from your code are automatically collected and logged, without implementing additional logging in your code. How would you achieve this with Data Science Jobs?

• A.Make sure that your code is using the standard logging library and then store all the logs to Object Storage at the end of the job.
• B.Create your own log group and use a third-party logging service to capture job run details for log collection and storing.
• C.On job creation, enable logging and select a log group. Then, select either a log or the option to enable automatic log creation.
• D.You can implement custom logging in your code by using the Data Science Jobs logging service.

You realize that your model deployment is about to reach its utilization limit. What would you do to avoid the issue before requests start to fail?

• A.Update the deployment to add more instances.
• B.Update the deployment to use a larger virtual machine (mare CPUs/memory).
• C.Reduce the load balancer bandwidth limit so that fewer requests come in.
• D.Update the deployment to use fewer instances.
• E.Delete the deployment.

You want to make your model more frugal to reduce the cost of collecting and processing data.
You plan to do this by removing features that are highly correlated. You would like to create a heat map that displays the correlation so that you can identify candidate features to remove.
Which Accelerated Data Science (ADS) SDK method is appropriate to display the comparability between Continuous and Categorical features?

• A.corr()
• B.correlation_ratio_plot()
• C.pearson_plot()
• D.cramersv_plot()

You have created a Data Science project in a compartment called Development and shared it with a group of collaborators. You now need to move the project to a different compartment called Production after completing the current development iteration.
Which statement is correct?

• A.You cannot move a project to a different compartment after it has been created.
• B.Moving a project to a different compartment requires deleting all its associated notebook sessions and models first.
• C.You can move a project to a different compartment without affecting its associated notebook sessions and models
• D.Moving a project to a different compartment also moves its associated notebook sessions and models to the new compartment.