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| Section | Objectives |
|---|---|
| Implement End-to-End Machine Learning Lifecycle | - Build, train, and evaluate machine learning models - Automate machine learning workflows and pipelines - Deploy models and consume model endpoints - Prepare and manage datasets - Save and manage models using Model Catalog |
| Apply MLOps Practices | - Monitor and maintain machine learning models - Use best practices for operationalizing ML solutions - Implement model lifecycle management |
| Use Related OCI Services | - Apply OCI services for data ingestion, storage, and processing - Integrate OCI Data and AI services - Design machine learning solutions for business use cases |
| OCI Data Science - Introduction and Configuration | - Understand OCI Data Science service concepts and architecture - Configure and manage Data Science resources - Use OCI Data Science notebooks and sessions |
| Design and Set Up Data Science Workspace | - Create and configure Data Science projects - Use Accelerated Data Science SDK and open source tools - Manage notebook sessions and compute resources |
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NEW QUESTION # 147
The Oracle AutoML pipeline automates hyperparameter tuning by training the model with different parameters in parallel. You have created an instance of Oracle AutoML as oracle_automl and now you want an output with all the different trials performed by Oracle AutoML. Which of the following commands gives you the results of all trials?
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Get all AutoML trial results.
Understand AutoML: Trials include hyperparameter tuning outcomes.
Evaluate Options:
A: print_trials()—Displays all trial results—correct.
B: visualize_tuning_trials()—Visualizes tuning, not full list.
C: visualize_adaptive_sampling_trials()—Specific to sampling, not all trials.
D: visualize_algorithm_selection_trials()—Specific to algorithms, not all.
Reasoning: A provides comprehensive trial output.
Conclusion: A is correct.
OCI AutoML documentation states: “print_trials() outputs a table of all trials performed, including hyperparameters and scores.” Visualization methods (B, C, D) focus on specific aspects—only A gives the full list.
1: Oracle Cloud Infrastructure AutoML Documentation, "Trial Output Methods".
NEW QUESTION # 148
You have received machine learning model training code, without clear information about the optimal shape to run the training on. How would you proceed to identify the optimal compute shape for your model training that provides a balanced cost and processing time?
Answer: B
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Find optimal compute shape balancing cost and time.
Approach: Iterative testing with metrics (e.g., CPU/memory usage, runtime).
Evaluate Options:
A: Tuning parameters when underutilized—focuses on model, not shape optimization.
B: Strongest shape—Costly, ignores balance; overkill likely.
C: Scale up from small shape when fully utilized—Balances cost/time effectively.
D: Random start with pre-tests—Unsystematic and inefficient.
Reasoning: C incrementally increases resources based on utilization, optimizing both factors.
Conclusion: C is correct.
OCI documentation advises: “To optimize compute shape for Jobs, start with a small shape, monitor utilization (e.g., CPU, memory) and runtime via OCI Monitoring. If fully utilized, scale up until performance plateaus—balancing cost and speed.” A misfocuses on model tuning, B wastes cost, and D lacks structure—only C aligns with this method.
1: Oracle Cloud Infrastructure Data Science Documentation, "Optimizing ComputeShapes for Jobs".
NEW QUESTION # 149
You are running a pipeline in the OCI Data Science service and want to override some of the pipeline's default settings. Which of the following statements about overriding pipeline defaults is true?
Answer: A
Explanation:
Detailed Answer in Step-by-Step Solution:
Understand OCI Data Science Pipelines: Pipelines automate ML workflows with configurable steps.
Check Override Mechanism: Defaults (e.g., compute shape, storage) can be modified before execution via the OCI Console, SDK, or CLI.
Evaluate Options:
A: False—Overrides can occur post-creation, before running.
B: False—Any authorized user, not just admins, can override defaults.
C: True—Settings can be adjusted before execution starts.
D: False—Defaults can be changed post-creation, pre-execution.
Conclusion: C is correct as it reflects the flexibility of pipeline configuration.
OCI Data Science Pipelines allow users to override default settings (e.g., compute resources, environment variables) before execution, as noted in the official documentation. This can be done via the UI or programmatically, offering flexibility beyond creation time (A) and without admin-only restrictions (B). (Oracle Cloud Infrastructure Data Science Pipelines Documentation, "Configuring Pipelines").
NEW QUESTION # 150
Triggering a PagerDuty notification as part of Monitoring is an example of what in the OCI Console?
Answer: D
Explanation:
Detailed Answer in Step-by-Step Solution:
Objective: Classify a PagerDuty notification in OCI Monitoring.
Understand OCI Monitoring: Involves events, rules, and actions for notifications.
Evaluate Options:
A: Action—executes a response (e.g., notify PagerDuty) when triggered—correct.
B: Rule—defines conditions for triggering actions—precedes the action.
C: Function—serverless code, not directly tied to notifications.
D: Event—state change triggering a rule, not the notification itself.
Reasoning: The notification is the action taken after an event/rule—fits A.
Conclusion: A is correct.
OCI documentation states: “Actions in the Monitoring service execute responses, such as sending notifications to PagerDuty, when a rule’s condition is met based on an event.” Rules (B) set conditions, Functions (C) are unrelated, and Events (D) are triggers—only Action (A) describes the notification step.
1: Oracle Cloud Infrastructure Monitoring Documentation, "Actions Overview".
NEW QUESTION # 151
You have been given a collection of digital files required for a business audit. They consist of several different formats that you would like to annotate using Oracle Cloud Infrastructure (OCI) Data Labeling. Which THREE types of files could this tool annotate?
Answer: A,D,E
Explanation:
Detailed Answer in Step-by-Step Solution:
Understand OCI Data Labeling Capabilities: OCI Data Labeling is designed to annotate data for machine learning, supporting specific file types like images, text documents, and videos.
Evaluate Options:
A . Video footage: Supported for tasks like object detection or action recognition.
B . Images: Supported for image classification, object detection, etc.
C . Typewritten document: Supported as text data for tasks like entity extraction or classification.
D . Purchase orders: While potentially text-based, this is ambiguous without format clarification (e.g., PDF, image). OCI supports text annotation, but “purchase orders” isn’t a specific file type—it’s assumed as text here.
E . Audio recording: Not supported, as OCI Data Labeling focuses on visual and textual data, not audio.
Select Three: A (video), B (images), and C (text documents) are explicitly supported file types.
OCI Data Labeling supports annotating datasets of images, text, and videos, as per the official documentation. Video footage (A) can be annotated for tasks like object tracking, images (B) for classification or detection, and typewritten documents (C) for text-based annotations (e.g., named entity recognition). Audio files (E) are not supported, and while purchase orders (D) could be text, the question specifies “typewritten document” as a clearer match. (Oracle Cloud Infrastructure Data Labeling Service Documentation, "Supported Data Types").
NEW QUESTION # 152
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