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NEW QUESTION: 1
Hyperledger is an open source project that came out of the ___________________________. It was created in order to help advance _____________________________blockchain technologies. It's a global open source collaboration involving leaders from numerous industries.
A. Linux Foundation, Cross Industry
B. Defense Industry, Military Communications
C. Linux Foundation, Military Communications
D. Defense Industry, Financial Oriented
E. Linux Foundation, Financial Oriented
Answer: A
Explanation:
Explanation
Hyperledger is an open source project that came out of the LF and was created in order to help advance cross-industry blockchain technologies. It's a global open source collaboration involving leaders from numerous industries.
NEW QUESTION: 2
注：このセクションでは、同じシナリオと問題についての質問が1つ以上表示されます。それぞれの質問は問題に対する独自の解決策を提示します、そしてあなたは解決策が述べられた目標を満たすかどうか決定しなければなりません。複数の解決策が問題を解決するかもしれません。解決策のどれも問題を解決しないことはまた可能性のあるです。
このセクションで質問に答えた後は、それに戻ることはできません。その結果、これらの質問はレビュー画面に表示されません。
注：この質問は同じシナリオを提示する一連の質問の一部です。シリーズの各質問には固有の解決策が含まれています。解決策が定められた目標を満たしているかどうかを判断します。
配信APIエラーを解決する必要があります。
あなたは何をするべきか？
A. Entity FrameworkのEnableRetryOnFailure機能を使用して、サーキットブレーカーパターンを実装します。
B. Entity FrameworkのEnableRetryOnFailure機能を使用して簡単な再試行を実装します。
C. Entity Frameworkの慣習的な実行方法を呼び出します。
D. Entity FrameworkのEnableRetryOnFailure機能を使用して指数バックオフを実装します。
Answer: D
Explanation:
説明/参照：
参考文献：
https://docs.microsoft.com/ja-jp/azure/sql-database/sql-database-develop-error-messages質問セット2
NEW QUESTION: 3
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:
Does the solution meet the goal?
A. Yes
B. No
Answer: B
Explanation:
Explanation
Note: Data used in pipeline can be produced by one step and consumed in another step by providing a PipelineData object as an output of one step and an input of one or more subsequent steps.
Compare with this example, the pipeline train step depends on the process_step_output output of the pipeline process step:
from azureml.pipeline.core import Pipeline, PipelineData
from azureml.pipeline.steps import PythonScriptStep
datastore = ws.get_default_datastore()
process_step_output = PipelineData("processed_data", datastore=datastore) process_step = PythonScriptStep(script_name="process.py", arguments=["--data_for_train", process_step_output], outputs=[process_step_output], compute_target=aml_compute, source_directory=process_directory) train_step = PythonScriptStep(script_name="train.py", arguments=["--data_for_train", process_step_output], inputs=[process_step_output], compute_target=aml_compute, source_directory=train_directory) pipeline = Pipeline(workspace=ws, steps=[process_step, train_step]) Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinedata?view=azu