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| Section | Objectives |
|---|---|
| AI Application Development (EI) | - Building AI Applications - Enterprise Intelligence (EI) Concepts - AI Service Integration |
| Huawei AI Ecosystem Tools | - MindSpore Framework Basics - AI Development Toolchain - Huawei Cloud AI Services |
| Model Deployment and Operations | - Monitoring and Maintenance - Inference Services - Model Deployment Strategies |
| Data Processing | - Feature Engineering - Data Labeling and Preparation - Data Collection and Cleaning |
| AI Fundamentals | - Common AI Use Cases in Industry - Introduction to Artificial Intelligence - AI Development Lifecycle |
| Deep Learning | - Neural Network Fundamentals - CNN and RNN Architectures - Model Training and Optimization |
| Machine Learning | - Unsupervised Learning
|
| Model Development with Huawei ModelArts | - AutoML Capabilities - ModelArts Platform Overview - Training Models on ModelArts |
Which of the following is not an acoustic feature of speech?
Correct Answer: D π³οΈ
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The development of large models should comply with ethical principles to ensure the legal, fair, and transparent use of data.
Correct Answer: A π³οΈ
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In the image recognition algorithm, the structure design of the convolutional layer has a great impact on its performance. Which of the following statements are true about the structure and mechanism of the convolutional layer? (Transposed convolution is not considered.)
Correct Answer: A,B,C,D π³οΈ
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When training a deep neural network model, a loss function measures the difference between the model's predictions and the actual labels.
Correct Answer: A π³οΈ
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The objective of -------- is to extract and classify named entities in a text into pre-defined classes such as names, organizations, locations, time expressions, monetary values, and percentages. (Enter the abbreviation.)
Reveal Solution Discussion 0Correct Answer:
NER
Explanation:
NER(Named Entity Recognition) is a core NLP task that involves locating and categorizing entities within text into predefined categories like persons, organizations, places, dates, monetary values, and percentages.
NER is widely used in information extraction, question answering, and knowledge graph construction.
Exact Extract from HCIP-AI EI Developer V2.5:
"NER identifies and classifies named entities in text into categories such as person names, organizations, locations, time expressions, and numeric values." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Sequence Labeling Tasks
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