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| Section | Objectives |
|---|---|
| Topic 1: OCI Data Science - Introduction and Configuration | - Configure and manage Data Science resources - Understand OCI Data Science service concepts and architecture - Use OCI Data Science notebooks and sessions |
| Topic 2: Apply MLOps Practices | - Use best practices for operationalizing ML solutions - Monitor and maintain machine learning models - Implement model lifecycle management |
| Topic 3: Design and Set Up Data Science Workspace | - Use Accelerated Data Science SDK and open source tools - Manage notebook sessions and compute resources - Create and configure Data Science projects |
| Topic 4: Implement End-to-End Machine Learning Lifecycle | - Prepare and manage datasets - Save and manage models using Model Catalog - Deploy models and consume model endpoints - Automate machine learning workflows and pipelines - Build, train, and evaluate machine learning models |
| Topic 5: Use Related OCI Services | - Design machine learning solutions for business use cases - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services |
>> Oracle 1Z0-1110-26최신버전 덤프공부문제 <<
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질문 # 105
You are a data scientist using Oracle AutoML to produce a model and you are evaluating the score metric for the model. Which of the following TWO prevailing metrics would you use for evaluating a multiclass classification model?
정답：C,D
설명：
Detailed Answer in Step-by-Step Solution:
Objective: Select two metrics for multiclass classification in AutoML.
Understand Multiclass Metrics: Focus on class-specific performance—classification, not regression.
Evaluate Options:
A . Recall: Measures true positives per class—key for multiclass—correct.
B . Mean squared error: Regression metric—incorrect.
C . F1 Score: Balances precision and recall—standard for multiclass—correct.
D . R-Squared: Regression fit—incorrect.
E . Explained variance: Regression metric—incorrect.
Reasoning: A and C assess classification accuracy across multiple classes—fit AutoML’s evaluation.
Conclusion: A and C are correct.
OCI AutoML documentation states: “For multiclass classification, common evaluation metrics include recall (A) for per-class sensitivity and F1 Score (C) for balanced performance.” B, D, and E are regression-focused—only A and C are supported and relevant per OCI’s AutoML metrics suite.
1: Oracle Cloud Infrastructure AutoML Documentation, "Evaluation Metrics for Classification".
질문 # 106
Select two reasons why it is important to rotate encryption keys when using Oracle Cloud Infrastructure (OCI) Vault to store credentials or other secrets.
정답：B,C
질문 # 107
As a data scientist, you are tasked with creating a model training job that is expected to take different hyperparameter values on every run. What is the most efficient way to set those parameters with Oracle Data Science Jobs?
정답：D
설명：
Detailed Answer in Step-by-Step Solution:
Objective: Efficiently vary hyperparameters in OCI Jobs.
Evaluate Options:
A: New job per run—Wastes setup time.
B: Code changes per job—Inefficient, error-prone.
C: Flexible params per run—Efficient, reusable—correct.
D: New job per run—Redundant effort.
Reasoning: C minimizes job creation, maximizes flexibility.
Conclusion: C is correct.
OCI documentation states: “For varying hyperparameters, configure a single Job with code accepting environment variables or command-line arguments (C), set per run—most efficient.” A and D over-create jobs, B ties params to code—only C optimizes.
1: Oracle Cloud Infrastructure Data Science Documentation, "Job Parameterization".
질문 # 108
Which statement is true about origin management in Web Application Firewall (WAF)?
정답：A
설명：
Detailed Answer in Step-by-Step Solution:
Objective: Determine truth about WAF origin management.
Understand WAF: Protects apps by routing traffic via origins.
Evaluate Statements:
A: Multiple origins—True; WAF supports this.
B: Single active origin—True; only one is active per policy.
Evaluate Options:
C: B only—False; A is true.
D: Both false—Incorrect.
E: Both true—Correct per OCI WAF.
F: A only—False; B is true.
Conclusion: E is correct.
OCI documentation states: “WAF allows defining multiple origins (A), but only one origin is active per WAF policy at a time (B)—both are true (E).” C, D, and F misalign—E matches OCI’s WAF origin management.
1: Oracle Cloud Infrastructure WAF Documentation, "Origin Management".
질문 # 109
Which statement about Oracle Cloud Infrastructure Multi-Factor Authentication (MFA) is NOT valid?
정답：D
설명：
Detailed Answer in Step-by-Step Solution:
Objective: Identify the invalid MFA statement.
Evaluate Options:
A: True—Users can’t disable MFA; admin-controlled.
B: False—Multiple devices can be registered—invalid.
C: True—Authenticator app is required.
D: True—Admins can disable MFA.
Reasoning: B contradicts OCI’s multi-device support.
Conclusion: B is incorrect.
OCI documentation states: “Users can register multiple devices for MFA (B is false), must use an authenticator app (C), and cannot disable MFA themselves (A)—admins can (D).” Only B is not valid per OCI’s IAM MFA policy.
1: Oracle Cloud Infrastructure IAM Documentation, "Multi-Factor Authentication".
질문 # 110
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만일Oracle 1Z0-1110-26인증시험을 첫 번째 시도에서 실패를 한다면 Oracle 1Z0-1110-26덤프비용 전액을 환불 할 것입니다. 만일 고객이 우리 제품을 구입하고 첫 번째 시도에서 성공을 하지 못 한다면 모든 정보를 확인 한 후에 구매 금액 전체를 환불 할 것 입니다. 이러한 방법으로 저희는 고객에게 어떠한 손해도 주지 않을 것을 보장합니다.
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