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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q25-Q30):

NEW QUESTION # 25
What feature of OCI Data Science provides an interactive coding environment for building and training models?

A. Model catalog
B. Accelerated Data Science (ADS) SDK
C. Conda environment
D. Notebook sessions

Answer: D

Explanation:
In OCI Data Science, Notebook sessions provide an interactive coding environment that is essential for building, training, and deploying machine learning models. These sessions allow data scientists to write and execute code in real time, offering a flexible environment for data exploration, model experimentation, and iterative development. The integration with various OCI services and support for popular machine learning frameworks further enhances the utility of Notebook sessions, making them a crucial tool in the data science workflow.

NEW QUESTION # 26
What can Oracle Cloud Infrastructure Document Understanding NOT do?

A. Classify documents into different types
B. Extract tables from documents
C. Extract text from documents
D. Generate transcript from documents

Answer: D

Explanation:
Oracle Cloud Infrastructure (OCI) Document Understanding service offers several capabilities, including extracting tables, classifying documents, and extracting text. However, it does not generate transcripts from documents. Transcription typically refers to converting spoken language into written text, which is a function associated with speech-to-text services, not document understanding services. Therefore, generating a transcript is outside the scope of what OCI Document Understanding is designed to do .

NEW QUESTION # 27
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Generation models
B. Embedding models
C. Translation models
D. Chat models

Answer: C

Explanation:
The OCI Generative AI service offers various categories of pretrained foundational models, including Embedding models, Chat models, and Generation models. These models are designed to perform a wide range of tasks, such as generating text, answering questions, and providing contextual embeddings. However, Translation models, which are typically used for converting text from one language to another, are not a category available in the OCI Generative AI service's current offerings. The focus of the OCI Generative AI service is more aligned with tasks related to text generation, chat interactions, and embedding generation rather than direct language translation.

NEW QUESTION # 28
What is the primary purpose of reinforcement learning?

A. Learning from outcomes to make decisions
B. Identifying patterns in data
C. Finding relationships within data sets
D. Making predictions from labeled data

Answer: A

Explanation:
Reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by taking actions in an environment to achieve a certain goal. The agent receives feedback in the form of rewards or penalties based on the outcomes of its actions, which it uses to learn and improve its decision-making over time. The primary purpose of reinforcement learning is to enable the agent to learn optimal strategies by interacting with its environment, thereby maximizing cumulative rewards. This approach is commonly used in areas such as robotics, game playing, and autonomous systems.

NEW QUESTION # 29
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?

A. Generation models
B. Embedding models
C. Translation models
D. Chat models

Answer: C

NEW QUESTION # 30
......

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