1z0-1110-23 試験問題を無料オンラインアクセス

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

Youare a data scientist working for a manufacturing company. You have developed a forecasting model to predict the sales demand in the upcoming months. You created a model artifact that contained custom logic requiring third party libraries. When you deployed the model, it failed to run because you did not include all the third party dependencies in the model artifact. What file should be modified to include the missing libraries?

• A.runtime.yaml
• B.model_artifact_validate.py
• C.requirements.txt
• D.score.py

Six months ago, you created and deployed a model that predicts customer churn for a call centre. Initially, it was yielding quality predictions. However, over the last two months, users are questioning the credibility of the predictions.
Which two methods would you employ to verify the accuracy of the model?

• A.Validate the model using recent data
• B.Operational monitoring
• C.Redeploy the model
• D.Drift monitoring
• E.Retrain the model

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.Moving a project to a different compartment also moves its associated notebook sessions and models to the new compartment.
• 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.You cannot move a project to a different compartment after it has been created.

Six months ago, you created and deployed a model that predicts customer churn for a call center. Initially, it was yielding quality predictions. However, over the last two months, users have been questioning the credibility of the predictions. Which TWO methods customer churn would you employ to verify the accuracy of the model?

• A.Validate the model using recent data
• B.Operational monitoring
• C.Redeploy the model
• D.Drift monitoring
• E.Retrain the model