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Oracle Cloud Infrastructure 2025 AI Foundations Associate Sample Questions (Q27-Q32):

NEW QUESTION # 27
In machine learning, what does the term "model training" mean?

A. Establishing a relationship between input features and output
B. Analyzing the accuracy of a trained model
C. Writing code for the entire program
D. Performing data analysis on collected and labeled data

Answer: A

Explanation:
In machine learning, "model training" refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.

NEW QUESTION # 28
Which is NOT a capability of OCI Vision's image analysis?

A. Object detection with bounding boxes
B. Locating and extracting text in images
C. Assigning classification labels to images
D. Translating text in images to another language

Answer: D

Explanation:
OCI Vision's image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision's image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision's core image analysis features.
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NEW QUESTION # 29
What does "fine-tuning" refer to in the context of OCI Generative AI service?

A. Upgrading the hardware of the AI clusters
B. Doubling the neural network layers
C. Encrypting the data for security reasons
D. Adjusting the model parameters to improve accuracy

Answer: D

Explanation:
Fine-tuning in the context of the OCI Generative AI service refers to the process of adjusting the parameters of a pretrained model to better fit a specific task or dataset. This process involves further training the model on a smaller, task-specific dataset, allowing the model to refine its understanding and improve its performance on that specific task. Fine-tuning is essential for customizing the general capabilities of a pretrained model to meet the particular needs of a given application, resulting in more accurate and relevant outputs. It is distinct from other processes like encrypting data, upgrading hardware, or simply increasing the complexity of the model architecture.

NEW QUESTION # 30
What is the purpose of the model catalog in OCI Data Science?

A. To create and switch between different environments
B. To deploy models as HTTP endpoints
C. To provide a preinstalled open source library
D. To store, track, share, and manage models

Answer: D

Explanation:
The primary purpose of the model catalog in OCI Data Science is to store, track, share, and manage machine learning models. This functionality is essential for maintaining an organized repository where data scientists and developers can collaborate on models, monitor their performance, and manage their lifecycle. The model catalog also facilitates model versioning, ensuring that the most recent and effective models are available for deployment. This capability is crucial in a collaborative environment where multiple stakeholders need access to the latest model versions for testing, evaluation, and deployment.

NEW QUESTION # 31
How does AI enhance human efforts?

A. By completely replacing human workers in all tasks
B. By processing data at a speed and effectiveness far beyond human capability
C. By deleting data humans need to handle
D. By increasing the physical strength of humans

Answer: B

Explanation:
AI enhances human efforts by processing large volumes of data quickly and accurately, performing complex computations that would be time-consuming or impossible for humans to handle manually. This allows humans to focus on more strategic, creative, and decision-making tasks, leveraging AI's ability to provide insights, automate repetitive processes, and support decision-making. AI does not physically enhance human capabilities, nor does it replace human workers in all tasks. Instead, it serves as an augmentation tool, amplifying human productivity and capabilities.

NEW QUESTION # 32
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