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NEW QUESTION: 1
What is the sum of all integers x, -37<X<35, such that ?
A. 0
B. 1
C. 2
D. 3
E. 4
Answer: B
NEW QUESTION: 2
Regarding the process described above, what is the most important recommendation you would make using IEEE 1044 as a guide? 2 credits
A. No mentioning of reproduceability
B. No priority or severity assigned
C. Incident numbering is manual rather than automated
D. No classification on type of incident
Answer: B
Explanation:
Topic 12, Scenario 12 "Automatic Teller Machine (ATM)"
You are a test manager in charge of integration, system and acceptance testing for a bank. You are working on a project to upgrade an existing ATM to allow customers to obtain cash advances from supported credit cards. The system should allow cash advances from 20EUR to 500EUR, inclusively, for all supported credit cards. The supported credit cards are American Express, VISA, Eurocard and Mastercard.
In the master test plan the following items are listed in the section named "items and/or features to be tested":
I All supported credit cards
II Language localization
II Valid and invalid advances
IV Usability
V Response time
NEW QUESTION: 3
会社は新しいWebサービスを展開していますが、そのサービスが何人の顧客を引き付けるか確信が持てません。
ただし、会社はダウンタイムを受け入れたくありません。
顧客の現在のセッションデータを追跡するために、ソリューションアーキテクトは会社に何を推奨できますか？
A. AWS CloudTrail
B. Amazon RDS
C. Amazon EC2
D. Amazon DynamoDB
Answer: D
Explanation:
Explanation
https://aws.amazon.com/blogs/aws/scalable-session-handling-in-php-using-amazon-dynamodb/
NEW QUESTION: 4
会社のソリューションを設計しています。このソリューションでは、客観的な分類にモデルトレーニングを使用します。
ソリューションを設計する必要があります。
何をお勧めしますか？
A. Spark MLibを使用するSparkアプリケーション。
B. Spark Streamingジョブ
C. Azure Cognitive Servicesアプリケーション
D. インタラクティブなSparkクエリ
E. Power BIモデル
Answer: A
Explanation:
Spark in SQL Server big data cluster enables AI and machine learning.
You can use Apache Spark MLlib to create a machine learning application to do simple predictive analysis on an open dataset.
MLlib is a core Spark library that provides many utilities useful for machine learning tasks, including utilities that are suitable for:
Classification
Regression
Clustering
Topic modeling
Singular value decomposition (SVD) and principal component analysis (PCA) Hypothesis testing and calculating sample statistics References:
https://docs.microsoft.com/en-us/azure/hdinsight/spark/apache-spark-machine-learning-mllib-ipython