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IBM S2000-027 - IBM Artificial Intelligence Fundamentals Specialty v1 Exam Braindumps

IBM S2000-027 - IBM Artificial Intelligence Fundamentals Specialty v1 Exam Braindumps

  • Certification Provider:IBM
  • Exam Code:S2000-027
  • Exam Name:IBM Artificial Intelligence Fundamentals Specialty v1 Exam Exam
  • Total Questions:276 Questions and Answers
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NEW QUESTION: 1
Betrachten Sie ein TAS zum Testen einer Desktop-Anwendung über die GUI. Alle Testfälle der automatisierten Testsuite enthalten zu Beginn (zum Erstellen der erforderlichen Objekte bei einer vorläufigen Konfiguration der Testumgebung und am Ende) die gleichen identischen Abfolgen von Schritten (um alles zu entfernen, was speziell für den Test selbst erstellt wurde die vorläufige Konfiguration der Testumgebung) Alle automatisierten Testfälle verwenden denselben Satz von Assertionsfunktionen aus einer gemeinsam genutzten Bibliothek, um die Werte in den GUI-Feldern (z. B. Textfeldern) zu überprüfen.
Was ist die BESTE Empfehlung zur Verbesserung der TAS?
A. Implementieren von Schlüsselwörtern mit höherer Granularität
B. Implementierung von Standard-Setup- und Teardown-Funktionen auf Testfall-Ebene
C. Übernahme einer Reihe von Standardüberprüfungsmethoden zur Verwendung durch alle automatisierten Tests
D. Verbesserung der Architektur der Anwendung, um ihre Testbarkeit zu verbessern
Answer: A

NEW QUESTION: 2
You need to recommend a solution for the HR users that meets the application requirements.
What should you recommend?
A. An App-V 5.0 client
B. A RemoteApp program on an RD Session Host server
C. An App-V 5.0 client on an RD Session Host server
D. Client Hyper-V
Answer: D
Explanation:
App-V does not support 16bit applications.
RemoteApp is running from a 64bit OS; 16bit apps are not supported on a 64bit OS.

NEW QUESTION: 3
Which blade enclosure component allows the aggregation of up to 16 iLO ports in an HPE c7000 enclosure?
A. HPE 40Gb Ethernet Switch
B. HPE Flex Fabric 20/40 F8 module
C. HPE Virtual Connect Enterprise Manager
D. HPE Onboard Administrator
Answer: D

NEW QUESTION: 4
あなたは広告会社で働いており、広告ブロックでのクリック率を予測するためのSparkMLモデルを開発しました。オンプレミスのデータセンターですべてを開発してきましたが、今では会社がGoogleCloudに移行しています。データセンターは間もなく閉鎖されるため、迅速なリフトアンドシフト移行が必要です。ただし、使用していたデータはBigQueryに移行されます。 Spark MLモデルを定期的に再トレーニングするため、既存のトレーニングパイプラインをGoogleCloudに移行する必要があります。あなたは何をするべきか?
A. 既存のSparkMLモデルのトレーニングにCloudDataprocを使用しますが、BigQueryから直接データの読み取りを開始します
B. 既存のSparkMLモデルのトレーニングにCloudMLEngineを使用する
C. Compute EngineでSparkクラスターを起動し、BigQueryからエクスポートされたデータでSparkMLモデルをトレーニングします
D. TensorFlowでモデルを書き直し、Cloud MLEngineの使用を開始します
Answer: B

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