最新1z0-1122-26考題將成為你通過Oracle Cloud Infrastructure 2026 AI Foundations Associate的利劍

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Oracle 1z0-1122-26 Exam Syllabus Topics:

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

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                                                  最新的 Oracle Cloud Infrastructure 1z0-1122-26 免費考試真題 (Q23-Q28):

                                                  問題 #23
                                                  What is the purpose of Attention Mechanism in Transformer architecture?

                                                  答案：B

                                                  解題說明：
                                                  The purpose of the Attention Mechanism in Transformer architecture is to weigh the importance of different words within a sequence and understand the context. In essence, the attention mechanism allows the model to focus on specific parts of the input sequence when producing an output, which is crucial for understanding context and maintaining coherence over long sequences. It does this by assigning different weights to different words in the sequence, enabling the model to capture relationships between words that are far apart and to emphasize relevant parts of the input when generating predictions.
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                                                  問題 #24
                                                  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?

                                                  答案：A

                                                  解題說明：
                                                  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.


                                                  問題 #25
                                                  What is the primary benefit of using Oracle Cloud Infrastructure Supercluster for AI workloads?

                                                  答案：A

                                                  解題說明：
                                                  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.


                                                  問題 #26
                                                  Lisa is working on a project that involves transcribing thousands of audio files stored in Oracle Cloud. She wants to process multiple files efficiently instead of transcribing them one by one. Which OCI Speech feature should Lisa use?

                                                  答案：C

                                                  解題說明：
                                                  OCI Speech supports batch transcription for efficiently processing prerecorded media. Lisa ' s key requirement is to process thousands of audio files without manually handling them individually. Oracle documentation explicitly identifies OCI Speech as supporting both real-time and batch transcription, while the OCI Speech documentation includes transcription jobs and large batch jobs among its supported workflows.
                                                  Oracle Docs Batch support therefore directly addresses high-volume processing of stored audio. Confidence scoring measures the service ' s certainty about recognized speech, timestamping associates transcript content with positions in the source recording, and profanity filtering controls how offensive language is represented.
                                                  Those capabilities enhance transcription output but do not provide the required multi-file processing mechanism. Consequently, Batch support is the appropriate OCI Speech capability for scalable transcription of Lisa ' s collection of audio files.


                                                  問題 #27
                                                  Which feature is NOT available as part of OCI Speech capabilities?

                                                  答案：D

                                                  解題說明：
                                                  OCI Speech capabilities are designed to be user-friendly and do not require extensive data science experience to operate. The service provides features such as transcribing audio and video files into text, offering grammatically accurate transcriptions, supporting multiple languages, and providing timestamped outputs.
                                                  These capabilities are built to be accessible to a broad range of users, making speech-to-text conversion seamless and straightforward without the need for deep technical expertise.


                                                  問題 #28
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