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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q35-Q40):

NEW QUESTION # 35
Which capability is supported by the Oracle Cloud Infrastructure Vision service?

A. Detecting vehicle number plates to issue speed citations
B. Generating realistic images from text
C. Analyzing historical data for unusual patterns
D. Detecting and preventing fraud in financial transactions

Answer: A

Explanation:
The Oracle Cloud Infrastructure (OCI) Vision service is designed for image analysis tasks, which includes the capability to detect and recognize objects, such as vehicle number plates. This functionality is particularly useful for applications such as automated enforcement of traffic laws, where the system can identify vehicles exceeding speed limits and issue citations based on the detected number plates. This capability leverages advanced computer vision techniques to process and analyze visual data, making it suitable for applications in public safety, transportation, and law enforcement.

NEW QUESTION # 36
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: D

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 # 37
You are part of the medical transcription team and need to automate transcription tasks. Which OCI AI service are you most likely to use?

A. Language
B. Document Understanding
C. Speech
D. Vision

Answer: C

Explanation:
For automating transcription tasks in a medical transcription team, the most appropriate OCI AI service to use would be the "Speech" service. This service is designed to convert spoken language into text, which is essential for transcribing spoken medical reports or consultations into written form. The OCI Speech service provides capabilities such as speech-to-text conversion, which is specifically tailored for handling audio input and producing accurate transcriptions.

NEW QUESTION # 38
You are working on a project for a healthcare organization that wants to develop a system to predict the severity of patients' illnesses upon admission to a hospital. The goal is to classify patients into three categories - Low Risk, Moderate Risk, and High Risk - based on their medical history and vital signs. Which type of supervised learning algorithm is required in this scenario?

A. Multi-Class Classification
B. Binary Classification
C. Clustering
D. Regression

Answer: A

Explanation:
In this healthcare scenario, where the goal is to classify patients into three categories-Low Risk, Moderate Risk, and High Risk-based on their medical history and vital signs, a Multi-Class Classification algorithm is required. Multi-class classification is a type of supervised learning algorithm used when there are three or more classes or categories to predict. This method is well-suited for situations where each instance needs to be classified into one of several categories, which aligns with the requirement to categorize patients into different risk levels.

NEW QUESTION # 39
What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?

A. Providing labels for the output neurons
B. Capturing the internal representation of the raw image data
C. Directly predicting the final output
D. Storing the input pixel values

Answer: B

Explanation:
In an Artificial Neural Network (ANN) designed for recognizing handwritten digits, the hidden layers serve the crucial function of capturing the internal representation of the raw image data. These layers learn to extract and represent features such as edges, shapes, and textures from the input pixels, which are essential for distinguishing between different digits. By transforming the input data through multiple hidden layers, the network gradually abstracts the raw pixel data into higher-level representations, which are more informative and easier to classify into the correct digit categories.

NEW QUESTION # 40
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Exam Sample 1z0-1122-24 Questions & 1z0-1122-24 Reliable Test Test

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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q35-Q40):

Quiz 2025 Oracle High-quality 1z0-1122-24: Exam Sample Oracle Cloud Infrastructure 2024 AI Foundations Associate Questions

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