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NEW QUESTION: 1
An engineer is converting all gateways to SIP and wants to ensure that the device is protected from traffic with
malicious intent? Which two parts must the engineer enable to protect the Cisco Unified Communications Manager
from SIP attacks on any newly created SIP trunks? (Choose two.)
A. SIP Max incoming Message Headers
B. SIP trunk TCP Port Throttle Threshold
C. SIP TCP Unused Connection Timer
D. SIP Station TCP Port Throttle Threshold
E. SIP Max incoming Message Size
F. Denial - of - Service Protection Flag
Answer: C,E

NEW QUESTION: 2
CPUベースのコンピューティングクラスターとAzureKubernetes Services（AKS）推論クラスターを含むAzure MachineLearningワークスペースがあります。分類モデルの作成に使用する予定のデータを含む表形式のデータセットを作成します。
Azure Machine Learningデザイナーを使用して、クライアントアプリケーションが新しいデータを送信し、応答として即時予測を取得することで分類モデルを利用できるWebサービスを作成する必要があります。
どの3つのアクションを順番に実行する必要がありますか？回答するには、適切なアクションをアクションのリストから回答領域に移動し、正しい順序で配置します。

Answer:
Explanation:

Explanation

Step 1: Create and start a Compute Instance
To train and deploy models using Azure Machine Learning designer, you need compute on which to run the training process, test the model, and host the model in a deployed service.
There are four kinds of compute resource you can create:
Compute Instances: Development workstations that data scientists can use to work with data and models.
Compute Clusters: Scalable clusters of virtual machines for on-demand processing of experiment code.
Inference Clusters: Deployment targets for predictive services that use your trained models.
Attached Compute: Links to existing Azure compute resources, such as Virtual Machines or Azure Databricks clusters.
Step 2: Create and run a training pipeline..
After you've used data transformations to prepare the data, you can use it to train a machine learning model.
Create and run a training pipeline
Step 3: Create and run a real-time inference pipeline
After creating and running a pipeline to train the model, you need a second pipeline that performs the same data transformations for new data, and then uses the trained model to inference (in other words, predict) label values based on its features. This pipeline will form the basis for a predictive service that you can publish for applications to use.
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/

NEW QUESTION: 3
最終製品のコンポーネントを決定するために、どのアプリケーションで部品表（BOM）を使用できますか？
この質問には3つの正解があります。
A. 製品原価計算
B. 外注
C. サードパーティの注文処理
D. 資材所要量計画
E. ベンダー委託
Answer: A,B,D

NEW QUESTION: 4
On Alcatel-Lucent 7750 SGW, which of the following statements is FALSE regarding the debugging of a given IMSI?
A. The APN value must be specified in the debug command.
B. The debugging allows the operator to analyze information and messages related to a given IMSI in real-time.
C. None of the above statements are false.
D. The debugging supports three levels of tracing detail.
E. The output may be filtered per APN or per reference point.
Answer: A