Authorized 1z0-1122-24 Certification & Study 1z0-1122-24 Materials
Authorized 1z0-1122-24 Certification & Study 1z0-1122-24 Materials
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Oracle Cloud Infrastructure 2024 AI Foundations Associate Sample Questions (Q41-Q46):
NEW QUESTION # 41
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. Clustering
- B. Binary Classification
- C. Multi-Class Classification
- D. Regression
Answer: C
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 # 42
What is the primary purpose of reinforcement learning?
- A. Identifying patterns in data
- B. Learning from outcomes to make decisions
- C. Making predictions from labeled data
- D. Finding relationships within data sets
Answer: B
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 # 43
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. Speech
- C. Document Understanding
- D. Vision
Answer: B
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 # 44
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?
- A. AI, ML, and DL are entirely separate fields with no overlap.
- B. AI is a subset of DL, which is a subset of ML.
- C. DL is a subset of AI, and ML is a subset of DL.
- D. ML is a subset of AI, and DL is a subset of ML.
Answer: D
Explanation:
Artificial Intelligence (AI) is the broadest field encompassing all technologies that enable machines to perform tasks that typically require human intelligence. Within AI, Machine Learning (ML) is a subset focused on the development of algorithms that allow systems to learn from and make predictions or decisions based on data. Deep Learning (DL) is a further subset of ML, characterized by the use of artificial neural networks with many layers (hence "deep").
In this hierarchy:
AI includes all methods to make machines intelligent.
ML refers to the methods within AI that focus on learning from data.
DL is a specialized field within ML that deals with deep neural networks.
NEW QUESTION # 45
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?
- A. Embedding models
- B. Translation models
- C. Generation models
- D. Chat models
Answer: B
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 # 46
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