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| Section | Weight | Objectives |
|---|---|---|
| Intro to AI Foundations | 10% | - Discuss AI Basics - Explain AI vs ML vs DL - Discuss AI Applications and Types of Data |
| Intro to ML Foundations | 15% | - Discuss Supervised Learning Fundamentals
- Discuss Reinforcement Learning Fundamentals - Discuss Unsupervised Learning Fundamentals |
| Intro to DL Foundations | 15% | - Explain Convolutional Models (CNN) - Explain Sequence Models (RNN and LSTM) - Discuss Deep Learning Fundamentals |
| Intro to Generative AI and LLMs | 15% | - Explain Transformers Fundamentals - Discuss Generative AI Overview - Explain Prompt Engineering and Instruction Tuning - Explain LLM Fine Tuning - Discuss Large Language Models Fundamentals |
| Get started with OCI AI Portfolio | 15% | - Discuss OCI ML Services Overview - Discuss OCI AI Infrastructure Overview - Explain Responsible AI - Discuss OCI AI Services Overview |
| OCI Generative AI and Oracle 23ai | 10% | - Discuss Oracle Vector Search - Discuss Autonomous Database Select AI - Describe OCI Generative AI Services |
| Intro to OCI AI Services | 20% | - OCI Vision - OCI Document Understanding - OCI Language - OCI Speech |
每個早晨都是全新一天的開始，給自己一個好心情，給自己一個新起點。擁有熱門的IT證照是你開啟IT之路的新起點。Oracle 1z0-1122-26 考題認證考試是個檢驗IT專業知識的認證考試。如果你想取得 1z0-1122-26 的認證資格，VCESoft 的 1z0-1122-26 考古題可以實現你的願望。在你考試之前使用我們提供的針對性培訓和測試練習題以及答案，短時間內你會有很大的收穫。
問題 #40
What is the primary purpose of reinforcement learning?
答案：C
解題說明：
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.
問題 #41
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 #42
Which is NOT a capability of OCI Vision ' s image analysis?
答案：C
解題說明：
OCI Vision ' s image analysis capabilities include locating and extracting text from images, assigning classification labels to images, and detecting objects with bounding boxes. However, translating text in images to another language is not a capability of OCI Vision ' s image analysis. This functionality typically requires an additional layer of processing, such as integration with a language translation service, which is beyond the scope of OCI Vision ' s core image analysis features.
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問題 #43
You are working on a multilingual public announcement system. Which AI task will you use to implement it?
答案：A
解題說明：
For a multilingual public announcement system, the AI task that would be most relevant is " Text to Speech " (TTS). This task involves converting written text into spoken words, which can then be broadcasted over public address systems in multiple languages.
Text to Speech technology is crucial for creating accessible and understandable announcements in different languages, especially in environments like airports, train stations, or public events where clear verbal communication is essential. The TTS system would be configured to support multiple languages, allowing it to deliver announcements to diverse audiences effectively .
問題 #44
In machine learning, what does the term " model training " mean?
答案：D
解題說明：
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.
問題 #45
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1z0-1122-26考試證照綜述: https://www.vcesoft.com/1z0-1122-26-pdf.html