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NEW QUESTION: 1
一連のラベル付き写真を使用するマルチクラス画像分類の深層学習モデルがあります。次のコードを作成して、モデルをトレーニングするときにハイパーパラメーター値を選択します。

次の各ステートメントについて、ステートメントがtrueの場合は[はい]を選択します。それ以外の場合は、[いいえ]を選択します。
注：それぞれの正しい選択は1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1: Yes
Hyperparameters are adjustable parameters you choose to train a model that govern the training process itself.
Azure Machine Learning allows you to automate hyperparameter exploration in an efficient manner, saving you significant time and resources. You specify the range of hyperparameter values and a maximum number of training runs. The system then automatically launches multiple simultaneous runs with different parameter configurations and finds the configuration that results in the best performance, measured by the metric you choose. Poorly performing training runs are automatically early terminated, reducing wastage of compute resources. These resources are instead used to explore other hyperparameter configurations.
Box 2: Yes
uniform(low, high) - Returns a value uniformly distributed between low and high Box 3: No Bayesian sampling does not currently support any early termination policy.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters

NEW QUESTION: 2
For security reasons, an administrator removes a user from the Active Directory domain used by all ESXi hosts for authentication. At the time the user is removed they are actively logged into an ESXi 5.x host through the vSphere Client.
What is true regarding this scenario?
A. The user immediately loses connectivity to and permissions on the host.
B. The user retains permissions on the host until the host is rebooted.
C. The user retains permissions on the object until the next time the user logs in to vCenter Server.
D. The user retains permissions and connectivity to the host for up to 24 hours.
Answer: B
Explanation:
http://pubs.vmware.com/vsphere-50/topic/com.vmware.ICbase/PDF/vsphereesxi-vcenter-server-50-security-guide.pdf

NEW QUESTION: 3
Which of the following searches would return a report of sales by product-name?
A. chart sales by product_name
B. chart sum(price) as sales by product_name
C. stats sum(price) as sales over product_name
D. timechart list(sales), values(product_name)
Answer: C
Explanation:
Reference:
http://hilllaneconsulting.co.uk/blog/?p=640