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NEW QUESTION: 1
You use the Azure Machine Learning SDK to run a training experiment that trains a classification model and calculates its accuracy metric.
The model will be retrained each month as new data is available.
You must register the model for use in a batch inference pipeline.
You need to register the model and ensure that the models created by subsequent retraining experiments are registered only if their accuracy is higher than the currently registered model.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Specify the model framework version when registering the model, and only register subsequent models if this value is higher.
B. Register the model with the same name each time regardless of accuracy, and always use the latest version of the model in the batch inferencing pipeline.
C. Specify a different name for the model each time you register it.
D. Specify a tag named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy tag value of the currently registered model.
E. Specify a property named accuracy with the accuracy metric as a value when registering the model, and only register subsequent models if their accuracy is higher than the accuracy property value of the currently registered model.
Answer: A,D
Explanation:
Explanation
E: Using tags, you can track useful information such as the name and version of the machine learning library used to train the model. Note that tags must be alphanumeric.
Reference:
https://notebooks.azure.com/xavierheriat/projects/azureml-getting-started/html/how-to-use-azureml/deployment/
NEW QUESTION: 2
How do you stop recording?
A. close the recording monitor
B. end the application under test
C. close RFT
D. click the Stop Recording button on the recording toolbar
Answer: D
NEW QUESTION: 3
AWS의 승인을 제한없이 한 지역에서 몇 개의 cg1.4xlarge 주문형 인스턴스를 실행할 수 있습니까?
A. 0
B. 1
C. 2
D. 3
Answer: D
Explanation:
Explanation
Generally, AWS EC2 allows running 20 on-demand instances and 100 spot instances at a time. This limit can be increased by requesting at
https://aws.amazon.com/contact-us/ec2-request. Excluding certain types of instances, the limit is lower than mentioned above. For cg1.4xlarge, the user can run only 2 on-demand instances at a time.
http://docs.aws.amazon.com/general/latest/gr/aws_service_limits.html#limits_ec2
NEW QUESTION: 4
A. Option C
B. Option B
C. Option A
D. Option D
Answer: B,D