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NEW QUESTION: 1
Project trade-offs vary between
A. quality, schedule and time
B. risk, cost and schedule.
C. cost, quality and schedule
D. direct cost, indirect cost, and resource availability
E. contract terms, scope and budget
Answer: C

NEW QUESTION: 2
Which three statements are true about installing and updating plug-ins in FileMaker Pro
12? (Choose three.)
A. A plug-in can be automatically installed on a client machine by using OnFirstWindowOpen to trigger a script that tests for the presence of the plug-in with the Install Plug-In File script step.
B. The Allow Solutions to Install Files checkbox must be enabled in the Plug-Ins tab of Preferences.
C. A plug-in can be removed using a script that includes the Uninstall Plug-In File script step.
D. The fmpplugin extended privilege must be enabled to install a new plug-in.
E. A plug-in must be stored on the server hosting the database to be automatically installed on client machines.
F. A FileMaker plug-in can be inserted into a container field and installed on a client machine.
Answer: A,B,F

NEW QUESTION: 3
クリックして各目標を展開します。 Azureポータルに接続するには、ブラウザーのアドレスバーに「https://portal.azure.com」と入力します。






すべてのタスクの実行が完了したら、[次へ]ボタンをクリックします。
[次へ]ボタンをクリックすると、ラボに戻ることはできません。残りの試験を完了する間、採点はバックグラウンドで行われます。
概観
試験の次のセクションはラボです。このセクションでは、ライブ環境で一連のタスクを実行します。ほとんどの機能はライブ環境と同じように使用できますが、一部の機能（コピーと貼り付け、外部のWebサイトに移動する機能など）は、設計上可能ではありません。
スコアリングは、ラボで述べられたタスクの実行結果に基づいています。つまり、タスクをどのように達成するかは関係ありません。タスクを正常に実行すると、そのタスクのクレジットを獲得できます。
ラボは個別に時間を計られておらず、この試験には、完了する必要のある複数のラボがある場合があります。各ラボを完了するのに必要なだけ時間を使用できます。ただし、時間を適切に管理して、指定された時間内にラボおよび試験の他のすべてのセクションを完了することができるようにする必要があります。
ラボ内の[次へ]ボタンをクリックして作品を送信すると、ラボに戻ることができなくなりますのでご注意ください。
ラボを開始するには
[次へ]ボタンをクリックしてラボを開始できます。
スティッキーセッションをサポートするcorp8548987n1という名前の関数アプリを作成する必要があります。このソリューションでは、App ServiceプランのAzure関連のコストを最小限に抑える必要があります。
Azureポータルから何をすべきですか？
Answer:
Explanation:
See explanation below.
Explanation
Step 1:
Select the New button found on the upper left-hand corner of the Azure portal, then select Compute > Function App.
Step 2:
Use the function app settings as listed below.
App name: corp8548987n1
Hosting plan: Azure App Service plan (required for sticky sessions)
Pricing tier of the App Service plan: Shared compute: Free
Step 3:
Select Create to provision and deploy the function app.
References:
https://docs.microsoft.com/en-us/azure/azure-functions/functions-create-function-app-portal

NEW QUESTION: 4
Which of the following are examples of hyperparameters? (Select 2 answers.)
A. Number of hidden layers
B. Biases
C. Number of nodes in each hidden layer
D. Weights
Answer: A,C
Explanation:
Explanation
If model parameters are variables that get adjusted by training with existing data, your hyperparameters are the variables about the training process itself. For example, part of setting up a deep neural network is deciding how many "hidden" layers of nodes to use between the input layer and the output layer, as well as how many nodes each layer should use. These variables are not directly related to the training data at all. They are configuration variables. Another difference is that parameters change during a training job, while the hyperparameters are usually constant during a job.
Weights and biases are variables that get adjusted during the training process, so they are not hyperparameters.
Reference: https://cloud.google.com/ml-engine/docs/hyperparameter-tuning-overview