Latest Oracle 1z0-1122-24 Exam Duration, Reliable 1z0-1122-24 Dumps Book
Latest Oracle 1z0-1122-24 Exam Duration, Reliable 1z0-1122-24 Dumps Book
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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q35-Q40):
NEW QUESTION # 35
What is the purpose of the model catalog in OCI Data Science?
- A. To deploy models as HTTP endpoints
- B. To provide a preinstalled open source library
- C. To create and switch between different environments
- 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 # 36
Which capability is supported by Oracle Cloud Infrastructure Language service?
- A. Analyzing text to extract structured information like sentiment or entities
- B. Translating text into speech
- C. Converting text into images
- D. Detecting objects and scenes in images
Answer: A
Explanation:
Oracle Cloud Infrastructure (OCI) Language service is specifically designed to analyze text and extract structured information such as sentiment, entities, key phrases, and language detection. This service provides natural language processing (NLP) capabilities that help users gain insights from unstructured text data. By identifying the sentiment (positive, negative, neutral) and recognizing entities (like names, dates, or places), the service enables businesses to process large volumes of text data efficiently, aiding in decision-making processes.
NEW QUESTION # 37
What does "fine-tuning" refer to in the context of OCI Generative AI service?
- A. Adjusting the model parameters to improve accuracy
- B. Upgrading the hardware of the AI clusters
- C. Doubling the neural network layers
- D. Encrypting the data for security reasons
Answer: A
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 # 38
Which AI domain is associated with tasks such as identifying the sentiment of text and translating text between languages?
- A. Natural Language Processing
- B. Computer Vision
- C. Anomaly Detection
- D. Natural Language Processing
Answer: A
Explanation:
Natural Language Processing (NLP) is the AI domain associated with tasks such as identifying the sentiment of text and translating text between languages. NLP focuses on enabling machines to understand, interpret, and generate human language in a way that is both meaningful and useful. This domain covers a wide range of applications, including text classification, language translation, sentiment analysis, and more, all of which involve processing and analyzing natural language data.
NEW QUESTION # 39
Which is NOT a capability of OCI Vision's image analysis?
- A. Translating text in images to another language
- B. Locating and extracting text in images
- C. Object detection with bounding boxes
- D. Assigning classification labels to images
Answer: A
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 # 40
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