최신업데이트버전1z0-1122-26시험패스가능한공부자료시험자료

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Oracle 1z0-1122-26 Exam Syllabus Topics:

Section	Objectives
Oracle AI and Machine Learning Services	- OCI AI Services 1. Language 2. Vision 3. Document Understanding 4. Speech - OCI Machine Learning Services 1. Machine learning capabilities in OCI 2. OCI Data Science and machine learning workflows - Oracle AI Stack 1. AI data and machine learning services 2. AI infrastructure
Generative AI and Large Language Models	- Generative AI Fundamentals 1. Generative AI use cases 2. Generative AI concepts and capabilities - Large Language Models 1. Language models and generative AI applications 2. LLM fundamentals
Artificial Intelligence and Machine Learning Fundamentals	- Deep Learning Fundamentals 1. Convolutional and sequence models 2. Neural networks - Machine Learning Fundamentals 1. Supervised and unsupervised learning 2. Machine learning models and architectures - Artificial Intelligence Concepts 1. AI fundamentals and terminology 2. AI use cases and applications
OCI Generative AI and Oracle Database AI Capabilities	- Oracle AI Database 1. AI capabilities in Oracle Database 2. Vector database concepts - OCI Generative AI 1. OCI Generative AI services 2. Generative AI models and applications - AI Application Frameworks 1. Language frameworks 2. Retrieval and AI application concepts

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최신 Oracle Cloud Infrastructure 1z0-1122-26 무료샘플문제 (Q21-Q26):

질문 # 21
In machine learning, what does the term " model training " mean?

A. Establishing a relationship between input features and output
B. Performing data analysis on collected and labeled data
C. Writing code for the entire program
D. Analyzing the accuracy of a trained model

정답：A

설명：
In machine learning, " model training " refers to the process of teaching a model to make predictions or decisions by learning the relationships between input features and the corresponding output. During training, the model is fed a large dataset where the inputs are paired with known outputs (labels). The model adjusts its internal parameters to minimize the error between its predictions and the actual outputs. Over time, the model learns to generalize from the training data to make accurate predictions on new, unseen data.

질문 # 22
A customer feedback analysis team needs to extract insights from thousands of online product reviews. They want to determine whether customers express positive or negative opinions about different aspects of a product or service. Which feature of OCI Language is helpful?

A. Sentiment analysis
B. Language detection
C. Key phrase extraction
D. Named entity recognition

정답：A

설명：
OCI Language provides pretrained natural language processing capabilities for analyzing unstructured text, including sentiment analysis. In this scenario, the requirement is specifically to determine whether customers express positive or negative opinions concerning individual aspects of a product or service. Oracle ' s OCI Language customer-feedback architecture describes extracting aspects from reviews and associating sentiments such as positive, negative, or neutral with those aspects. Oracle Docs Key phrase extraction identifies important topics or phrases, named entity recognition identifies entities such as organizations, people, or locations, and language detection determines the language in which content is written. None directly evaluates customer opinion. Sentiment analysis therefore precisely matches the business requirement because it transforms subjective review content into structured sentiment information that can be analyzed at scale.

질문 # 23
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 delivers exceptional performance and scalability for complex AI tasks.
C. It offers seamless integration with social media platforms.
D. It is ideal for tasks such as text-to-speech conversion.

정답：B

설명：
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.

질문 # 24
Which statement describes the Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure Document Understanding?

A. It recognizes and extracts text from a document.
B. It converts audio files into text.
C. It enhances the visual quality of documents.
D. It provides real-time translation of text.

정답：A

설명：
The Optical Character Recognition (OCR) feature of Oracle Cloud Infrastructure (OCI) Document Understanding recognizes and extracts text from documents. This capability is fundamental for converting printed or handwritten text into a machine-readable format, allowing for further processing, such as text analysis, search, and archiving. OCI ' s OCR is an essential tool in automating document processing workflows, enabling businesses to digitize and manage their documents efficiently.

질문 # 25
Which algorithm is primarily used for adjusting the weights of connections between neurons during the training of an Artificial Neural Network (ANN)?

A. Gradient Descent
B. Random Forest
C. Backpropagation
D. Support Vector Machine

정답：C

설명：
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.

질문 # 26
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