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NEW QUESTION: 1
あなたの会社には、WPA2-Enterpriseを使用するワイヤレスアクセスポイントがあります。
ワイヤレスアクセスポイントに接続するには、コンピューターを構成する必要があります。
最初に何をすべきですか？
A. Windows構成デザイナーでプロビジョニングパッケージを作成します。
B. パスフレーズを要求します。
C. 証明書を要求してインストールします。
D. 接続マネージャー管理キット（CMAK）パッケージを作成します。
Answer: B
Explanation:
Explanation
References:
https://support.microsoft.com/en-za/help/17137/windows-setting-up-wireless-network

NEW QUESTION: 2
What is the significance of using a specific LUN type when creating LUNs manually on a NetApp storage system?
A. The LUN types allow the appropriate host operating systems to use the LUN. For example, a VMware type LUN cannot be read from /written to using a Solaris host.
B. The LUNs offset, size of the prefix and suffix is determined by the LUN type, which differs for different operating systems.
C. The host operating system will panic when the "wrong" LUN type is selected on the NetApp storage system.
D. The LUN types are merely for administrative ease of use and the LUN types can be changed on the fly after creation.
Answer: C

NEW QUESTION: 3
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. Register the model with the same name each time regardless of accuracy, and always use the latest
B. Specify the model framework version when registering the model, and only register subsequent models if this value is higher.
C. Specify a different name for the model each time you register it.
D. 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.
E. 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.
Answer: B,E
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/register-model-create-image-deploy-service/register-model-create-image-deploy-service.ipynb