Huawei : H13-321_V2.5 Questions & Answers
Updated: Sep 25, 2026
No. of Questions: 62 Questions & Answers with Testing Engine
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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| AI Application Development (EI) | - AI Service Integration - Enterprise Intelligence (EI) Concepts - Building AI Applications |
| Model Development with Huawei ModelArts | - Training Models on ModelArts - AutoML Capabilities - ModelArts Platform Overview |
| AI Fundamentals | - Introduction to Artificial Intelligence - AI Development Lifecycle - Common AI Use Cases in Industry |
| Deep Learning | - CNN and RNN Architectures - Neural Network Fundamentals - Model Training and Optimization |
| Machine Learning | - Unsupervised Learning
|
| Model Deployment and Operations | - Model Deployment Strategies - Inference Services - Monitoring and Maintenance |
| Huawei AI Ecosystem Tools | - AI Development Toolchain - Huawei Cloud AI Services - MindSpore Framework Basics |
| Data Processing | - Data Labeling and Preparation - Feature Engineering - Data Collection and Cleaning |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
The mAP evaluation metric in object detection combines accuracy and recall.
- A. FALSE
- B. TRUE
Correct Answer: A 🗳️
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The natural language processing field usually uses distributed semantic representation to represent words.
Each word is no longer a completely orthogonal 0-1 vector, but a point in a multi-dimensional real number space, which is specifically represented as a real number vector.
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
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Maximum likelihood estimation (MLE) can be used for parameter estimation in a Gaussian mixture model (GMM).
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
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Among image preprocessing techniques, gamma correction is a common non-linear brightness adjustment method. Which of the following statements are true about the application and features of gamma correction?
- A. Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.
- B. When # < 1, the input high grayscale range is compressed, and the low grayscale range is stretched, enhancing the dark areas while compressing the bright areas.
- C. When # > 1, the input low grayscale range is compressed, and the high grayscale range is stretched, enhancing the bright areas while compressing the dark areas.
- D. Gamma correction applies only to grayscale images and does not apply to color images.
Correct Answer: A,B,C 🗳️
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Maximum likelihood estimation (MLE) requires knowledge of the sample data's distribution type.
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
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