[2025年04月05日] 最速合格には素晴らしい1z0-1122-24無料テストPDF本日更新です
無料でゲット！最新の2025年最新の有効な練習Oracle Cloud 1z0-1122-24問題と解答でテストエンジン
質問 # 11
What distinguishes Generative AI from other types of AI?
- A. Generative AI focuses on making decisions based on user interactions.
- B. Generative AI creates diverse content such as text, audio, and images by learning patterns from existing data.
- C. Generative AI uses algorithms to predict outcomes based on past data.
- D. Generative AI involves training models to perform tasks without human intervention.
正解：B
解説：
Generative AI is distinct from other types of AI in that it focuses on creating new content by learning patterns from existing data. This includes generating text, images, audio, and other types of media. Unlike AI that primarily analyzes data to make decisions or predictions, Generative AI actively creates new and original outputs. This ability to generate diverse content is a hallmark of Generative AI models like GPT-4, which can produce human-like text, create images, and even compose music based on the patterns they have learned from their training data.
質問 # 12
Which is NOT a category of pretrained foundational models available in the OCI Generative AI service?
- A. Translation models
- B. Embedding models
- C. Generation models
- D. Chat models
正解：A
解説：
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.
質問 # 13
Which AI domain can be employed for identifying patterns in images and extract relevant features?
- A. Computer Vision
- B. Anomaly Detection
- C. Speech Processing
- D. Natural Language Processing
正解：A
解説：
Computer Vision is the AI domain specifically employed for identifying patterns in images and extracting relevant features. This field focuses on enabling machines to interpret and understand visual information from the world, automating tasks that the human visual system can perform, such as recognizing objects, analyzing scenes, and detecting anomalies. Techniques in Computer Vision are widely used in applications ranging from facial recognition and image classification to medical image analysis and autonomous vehicles.
質問 # 14
What can Oracle Cloud Infrastructure Document Understanding NOT do?
- A. Extract text from documents
- B. Classify documents into different types
- C. Extract tables from documents
- D. Generate transcript from documents
正解：D
解説：
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 .
質問 # 15
What is the primary benefit of using the OCI Language service for text analysis?
- A. It requires extensive machine learning expertise to use.
- B. It provides image processing capabilities.
- C. It allows for text analysis at scale without machine learning expertise.
- D. It only works with structured data.
正解：C
解説：
The primary benefit of using the OCI Language service for text analysis is its ability to scale text analysis without requiring users to have extensive machine learning expertise. The service abstracts the complexities of machine learning, allowing businesses to easily process and analyze large amounts of text data through pre-built models. This accessibility makes it possible for a broader range of users to leverage advanced text analysis capabilities, facilitating insights from textual data without needing to develop and train models from scratch.
質問 # 16
What is the main function of the hidden layers in an Artificial Neural Network (ANN) when recognizing handwritten digits?
- A. Capturing the internal representation of the raw image data
- B. Storing the input pixel values
- C. Providing labels for the output neurons
- D. Directly predicting the final output
正解：A
解説：
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.
質問 # 17
Which feature is NOT supported as part of the OCI Language service's pretrained language processing capabilities?
- A. Language Detection
- B. Sentiment Analysis
- C. Text Classification
- D. Text Generation
正解：D
解説：
The OCI Language service offers several pretrained language processing capabilities, including Text Classification, Sentiment Analysis, and Language Detection. However, it does not natively support Text Generation as a part of its core language processing capabilities. Text Generation typically involves creating new content based on input prompts, which is a feature more commonly associated with models specifically designed for natural language generation.
質問 # 18
What key objective does machine learning strive to achieve?
- A. Improving computer hardware
- B. Creating algorithms to solve complex problems
- C. Enabling computers to learn and improve from experience
- D. Explicitly programming computers
正解：C
解説：
The key objective of machine learning is to enable computers to learn from experience and improve their performance on specific tasks over time. This is achieved through the development of algorithms that can learn patterns from data and make decisions or predictions without being explicitly programmed for each task. As the model processes more data, it becomes better at understanding the underlying patterns and relationships, leading to more accurate and efficient outcomes.
質問 # 19
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. Binary Classification
- B. Regression
- C. Multi-Class Classification
- D. Clustering
正解：C
解説：
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.
質問 # 20
How does AI enhance human efforts?
- A. By deleting data humans need to handle
- B. By increasing the physical strength of humans
- C. By completely replacing human workers in all tasks
- D. By processing data at a speed and effectiveness far beyond human capability
正解：D
解説：
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.
質問 # 21
What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?
- A. It provides a cost-effective solution for simple AI tasks.
- B. It is ideal for tasks such as text-to-speech conversion.
- C. It delivers exceptional performance and scalability for complex AI tasks.
- D. It offers seamless integration with social media platforms.
正解：C
解説：
Oracle Cloud Infrastructure Supercluster is designed to deliver exceptional performance and scalability for complex AI tasks. The primary benefit of this infrastructure is its ability to handle demanding AI workloads, offering high-performance computing (HPC) capabilities that are crucial for training large-scale AI models and processing massive datasets. The architecture of the Supercluster ensures low-latency networking, efficient resource allocation, and high-throughput processing, making it ideal for AI tasks that require significant computational power, such as deep learning, data analytics, and large-scale simulations.
質問 # 22
What are Convolutional Neural Networks (CNNs) primarily used for?
- A. Image classification
- B. Time series prediction
- C. Text processing
- D. Image generation
正解：A
解説：
Convolutional Neural Networks (CNNs) are primarily used for image classification and other tasks involving spatial data. CNNs are particularly effective at recognizing patterns in images due to their ability to detect features such as edges, textures, and shapes across multiple layers of convolutional filters. This makes them the model of choice for tasks such as object recognition, image segmentation, and facial recognition.
CNNs are also used in other domains like video analysis and medical image processing, but their primary application remains in image classification.
質問 # 23
Which AI Ethics principle leads to the Responsible AI requirement of transparency?
- A. Prevention of harm
- B. Explicability
- C. Fairness
- D. Respect for human autonomy
正解：B
質問 # 24
What would you use Oracle AI Vector Search for?
- A. Store business data in a cloud database.
- B. Query data based on keywords.
- C. Manage database security protocols.
- D. Query data based on semantics.
正解：D
解説：
Oracle AI Vector Search is designed to query data based on semantics rather than just keywords. This allows for more nuanced and contextually relevant searches by understanding the meaning behind the words used in a query. Vector search represents data in a high-dimensional vector space, where semantically similar items are placed closer together. This capability makes it particularly powerful for applications such as recommendation systems, natural language processing, and information retrieval where the meaning and context of the data are crucial .
質問 # 25
Which AI Ethics principle leads to the Responsible AI requirement of transparency?
- A. Prevention of harm
- B. Explicability
- C. Fairness
- D. Respect for human autonomy
正解：B
解説：
Explicability is the AI Ethics principle that leads to the Responsible AI requirement of transparency. This principle emphasizes the importance of making AI systems understandable and interpretable to humans. Transparency is a key aspect of explicability, as it ensures that the decision-making processes of AI systems are clear and comprehensible, allowing users to understand how and why a particular decision or output was generated. This is critical for building trust in AI systems and ensuring that they are used responsibly and ethically.
Top of Form
Bottom of Form
質問 # 26
Which statement best describes the relationship between Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL)?
- A. ML is a subset of AI, and DL is a subset of ML.
- B. DL is a subset of AI, and ML is a subset of DL.
- C. AI is a subset of DL, which is a subset of ML.
- D. AI, ML, and DL are entirely separate fields with no overlap.
正解：A
解説：
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.
質問 # 27
Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?
- A. Support Vector Machine
- B. Gradient Descent
- C. Backpropagation
- D. Random Forest
正解：C
解説：
Backpropagation is the algorithm primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN). It is a supervised learning algorithm that calculates the gradient of the loss function with respect to each weight by applying the chain rule, propagating the error backward from the output layer to the input layer. This process updates the weights to minimize the error, thus improving the model's accuracy over time.
Gradient Descent is closely related as it is the optimization algorithm used to adjust the weights based on the gradients computed by backpropagation, but backpropagation is the specific method used to calculate these gradients.
質問 # 28
......
Oracle 1z0-1122-24 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
| トピック 5 |
|
1z0-1122-24問題集PDFで100%合格保証付き：https://jp.fast2test.com/1z0-1122-24-premium-file.html