Professional-Machine-Learning-Engineer 무료 덤프문제 온라인 액세스

You have developed a fraud detection model for a large financial institution using Vertex AI. The model achieves high accuracy, but the stakeholders are concerned about the model's potential for bias based on customer demographics. You have been asked to provide insights into the model's decision-making process and identify any fairness issues. What should you do?

• A.Compile a dataset of unfair predictions. Use Vertex AI Vector Search to identify similar data points in the model's predictions. Report these data points to the stakeholders.
• B.Create feature groups using Vertex AI Feature Store to segregate customer demographic features and non-demographic
• C.Enable Vertex AI Model Monitoring to detect training-serving skew. Configure an alert to send an email when the skew or drift for a modes feature exceeds a predefined threshold. Re-train the model by appending new data to existing raining data.
• D.Use feature attribution in Vertex AI to analyze model predictions and the impact of each feature on the model's predictions.

You developed a custom model by using Vertex AI to forecast the sales of your company's products based on historical transactional data. You anticipate changes in the feature distributions and the correlations between the features in the near future. You also expect to receive a large volume of prediction requests. You plan to use Vertex AI Model Monitoring for drift detection and you want to minimize the cost. What should you do?

• A.Use the features for monitoring. Set a monitoring-frequency value that is higher than the default.
• B.Use the features and the feature attributions for monitoring. Set a monitoring-frequency value that is lower than the default.
• C.Use the features for monitoring. Set a prediction-sampling-rate value that is closer to 1 than 0.
• D.Use the features and the feature attributions for monitoring. Set a prediction-sampling-rate value that is closer to 0 than 1.

You are deploying a new version of a model to a production Vertex Al endpoint that is serving traffic. You plan to direct all user traffic to the new model. You need to deploy the model with minimal disruption to your application. What should you do?

• A.1. Create a new model. Set it as the default version. Upload the model to Vertex AI Model Registry
  2. Deploy the new model to the existing endpoint
• B.1. Create a new model. Set the parentModel parameter to the model ID of the currently deployed model. Upload the model to Vertex AI Model Registry.
  2. Deploy the new model to the existing endpoint, and set the new model to 100% of the traffic
• C.1. Create a new endpoint
  2. Create a new model. Set the parentModel parameter to the model ID of the currently deployed model and set it as the default version. Upload the model to Vertex AI Model Registry
  3. Deploy the new model to the new endpoint, and set the new model to 100% of the traffic.
• D.1. Create a new endpoint
  2. Create a new model. Set it as the default version. Upload the model to Vertex AI Model Registry
  3. Deploy the new model to the new endpoint
  4. Update Cloud DNS to point to the new endpoint

You are developing an ML model intended to classify whether X-ray images indicate bone fracture risk. You have trained a ResNet architecture on Vertex AI using a TPU as an accelerator, however you are unsatisfied with the training time and memory usage. You want to quickly iterate your training code but make minimal changes to the code. You also want to minimize impact on the model's accuracy. What should you do?

• A.Reduce the dimensions of the images used in the model.
• B.Reduce the number of layers in the model architecture.
• C.Configure your model to use bfloat16 instead of float32.
• D.Reduce the global batch size from 1024 to 256.

You work for a pharmaceutical company based in Canada. Your team developed a BigQuery ML model to predict the number of flu infections for the next month in Canada. Weather data is published weekly, and flu infection statistics are published monthly. You need to configure a model retraining policy that minimizes cost. What should you do?

• A.Download the weather and flu data each week. Configure Cloud Scheduler to execute a Vertex AI pipeline to retrain the model every month.
• B.Download the weather and flu data each week. Configure Cloud Scheduler to execute a Vertex AI pipeline to retrain the model weekly.
• C.Download the weather data each week, and download the flu data each month. Deploy the model to a Vertex AI endpoint with feature drift monitoring, and retrain the model if a monitoring alert is detected.
• D.Download the weather and flu data each month. Configure Cloud Scheduler to execute a Vertex AI pipeline to retrain the model monthly.