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NEW QUESTION: 1
A customer needs an entry -level SAN that supports SSD acceleration.
Which HPE product satisfies these criteria?
A. HPE StoreEasy 1840
B. HPE StoreEasy 1450
C. MSA 2042
D. MAS 1040
Answer: C
Explanation:

NEW QUESTION: 2
You need to implement early stopping criteria as suited in the model training requirements.
Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.

Answer:
Explanation:

Explanation:
You need to implement an early stopping criterion on models that provides savings without terminating promising jobs.
Truncation selection cancels a given percentage of lowest performing runs at each evaluation interval. Runs are compared based on their performance on the primary metric and the lowest X% are terminated.
Example:
from azureml.train.hyperdrive import TruncationSelectionPolicy
early_termination_policy = TruncationSelectionPolicy(evaluation_interval=1, truncation_percentage=20, delay_evaluation=5) Incorrect Answers:
Bandit is a termination policy based on slack factor/slack amount and evaluation interval. The policy early terminates any runs where the primary metric is not within the specified slack factor / slack amount with respect to the best performing training run.
Example:
from azureml.train.hyperdrive import BanditPolicy
early_termination_policy = BanditPolicy(slack_factor = 0.1, evaluation_interval=1, delay_evaluation=5 References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters

NEW QUESTION: 3
DevOpsエンジニアには、すべてが異なるログ形式を生成するいくつかのレガシーアプリケーションがあります。エンジニアは、クエリと分析のためにフォーマットをAmazon S3に書き込む前に標準化する必要があります。最も低いコストでこの要件を満たすにはどうすればよいですか？
A. アプリケーションにログをAmazon QuickSightに送信してから、Amazon QuickSight SPICEエンジンを使用してログを正規化します。 Amazon QuickSightから直接分析を行います。
B. Amazon S3にログを保持し、Amazon Redshift Spectrumを使用して、ログを適切に正規化します。
C. アプリケーションからログをAmazon EMRクラスターに送信し、ログを正規化してからAmazon S3に送信します。
D. 各サーバーでAmazon Kinesis Agentを使用してログをアップロードし、Amazon Kinesis Data FirehoseでAWS Lambda関数を使用してログを正規化してからAmazonに書き込みます。
Answer: D

NEW QUESTION: 4
Which one of the following options describes the runtime flow starting from the client browser in a clustered WebSphere Application Server Network Deployment topology?
A. Application server -> node agent -> deployment manager -> load balancer
B. Load balancer -> HTTP server -> HTTP server plug-in -> application server
C. Deployment manager -> node agent -> HTTP server plug-in -> HTTP server
D. HTTP server -> job manager -> admin agent -> HTTP server plug-in
Answer: B