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Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Huawei AI Development Platform (ModelArts) | - ModelArts usage and workflow - Dataset management - Model training and deployment on ModelArts |
| AI Application Deployment and Operations | - AI service monitoring and optimization - Inference service deployment |
| Data Processing and Analysis | - Data preprocessing techniques - Feature engineering |
| AI Model Development | - Model training and evaluation - Hyperparameter tuning |
| Artificial Intelligence Fundamentals | - Machine learning basics - Deep learning fundamentals - Introduction to AI concepts |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
Which of the following options are Huawei Ascend AI chips? (Multiple choice)
- A. Shengteng 910
- B. Shengteng 510
- C. Shengteng 310
- D. Shengteng 710
Correct Answer: A,C 🗳️
Which of the following is an inference server provided by Shengteng Computing to its customers and partners?
- A. Atlas 800 model
- B. Atlas 300 model
- C. Atlas 800 model
- D. Atlas 800 model
Correct Answer: A 🗳️
ModelArts is a one-stop AI development platform built around the AI development process. Users can customize and develop AI models based on ModelArts . ModelArts ' capabilities cover all aspects of AI development.
- A. True
- B. False
Correct Answer: A 🗳️
Which of the following statements about participles is incorrect?
- A. Chinese is different from English natural word segmentation. Chinese word segmentation is a basic step in text processing. The performance of word segmentation directly affects the performance of other modules such as part of speech and syntax tree.
- B. The purpose of statistical segmentation is to perform probability calculation on the segmentation results and obtain the segmentation method with the highest probability.
- C. In actual engineering applications, word segmentation generally only uses one method.
- D. Rule-based word segmentation is simple and efficient, but dictionary maintenance is difficult.
Correct Answer: C 🗳️
Which of the following methods can improve the fitting ability of neural networks? (Multiple choice)
- A. Add a certain number of hidden layers
- B. Adding residual blocks to neural networks
- C. Reduce the number of neurons
- D. Use non-linear activation functions
Correct Answer: A,B,D 🗳️
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