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Exam Code:
Generative-AI-Leader
Exam Name:
Google Cloud Certified - Generative AI Leader Exam
Questions:
94 Q&A
Product Type:

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NEW QUESTION: 1
While you are using the text pool, then what statements you will take into consideration?
There are 2 correct answers to this question.
A. Instead, you should use modeled texts from the text pool of the UI component.
B. Texts for the end user should also never be created by concatenating variables or variables and literals, because the order of the elements may have to change in different languages.
C. One should not use modeled texts from the text pool of the UI component
D. Texts for the end user should also be created by concatenating variables, because the order of the elements may have to change in different languages.
Answer: A,B

NEW QUESTION: 2
A pre-sales Technical Delivery Assessment is required for which of the following systems?
A. Power 770, 780, and 795
B. Power 720, 740, 750, 760, 770, 780, and 795
C. Power 760, 770, 780, and 795
D. Power 750, 760, 770, 780, and 795
Answer: A

NEW QUESTION: 3
In the first phase of IKE V1, the pre-shared key master mode exchange process, in which message is the SA payload sent?
A. Message 7 and Message 8
Note: IKE V1 Phase 1 mainly negotiates the following three tasks: First, negotiate the parameters used to establish IKE SA: encryption algorithm, integrity verification algorithm, identity authentication method and authentication word, DH group, IKE SA life cycle, etc. . These parameters are defined in the IKE security proposal. The second is to use the DH algorithm to exchange information related to the key (the material for generating various keys), and the peer devices can use each of the key information to generate a symmetric key for ISAKMP message encryption and verification. The third is to verify each other's identity and use a pre-shared key or digital certificate to verify identity.
B. Message 5 and Message 6
C. Message 3 and Message 4
D. Message 1 and Message 2
Answer: D

NEW QUESTION: 4
Azure Machine Learning Studioで多重線形回帰モデルを作成しています。
いくつかの独立変数は高度に相関しています。
すべてのデータに対して効果的な特徴エンジニアリングを行うための適切な方法を選択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、正しい順序に並べます。

Answer:
Explanation:

Explanation

Step 1: Use the Filter Based Feature Selection module
Filter Based Feature Selection identifies the features in a dataset with the greatest predictive power.
The module outputs a dataset that contains the best feature columns, as ranked by predictive power. It also outputs the names of the features and their scores from the selected metric.
Step 2: Build a counting transform
A counting transform creates a transformation that turns count tables into features, so that you can apply the transformation to multiple datasets.
Step 3: Test the hypothesis using t-Test
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/studio-module-reference/filter-based-feature-selec
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/build-counting-transform

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