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Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Topic 2: Theoretical Knowledge and Applications of Image Processing | 26% | - Image recognition, detection and segmentation - Image preprocessing and feature extraction - Convolutional neural networks - Computer vision overview |
| Topic 3: Overview of ModelArts | 4% | - ModelArts platform architecture - Development and deployment workflow |
| Topic 4: Neural Network Basics | 4% | - Network training and optimization - Artificial neural network principles - Deep learning fundamentals |
| Topic 5: Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Topic 6: Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | |
| Topic 7: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Common NLP tasks and applications - Text processing and representation - NLP core concepts |
| Topic 8: Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Topic 9: ModelArts Platform Development Experiment | 10% | |
| Topic 10: Theoretical Knowledge and Applications of Speech Processing | 10% | - Speech recognition and synthesis - Acoustic and language models - Speech processing basics |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. Which of the following options are correct about the description of rectangular window and Hamming window? (Multiple choice)
A) The main lobe width of the Hamming window is larger than that of the rectangular window, and has a higher spectral resolution (the rectangular frame has a higher spectral resolution)
B) The Hamming window can effectively overcome the leakage phenomenon and has the widest application range.
C) The rectangular window has better smoothness, but the waveform details are lost and leakage occurs (Yes, new version PPT page 253)
D) The side lobe peak of the rectangular window is large, so its spectrum leakage is more serious
2. The HMM algorithm is a generative model, and CRF is a discriminative model. Both can be used for sequential labeling.
A) True
B) False
3. The back propagation algorithm is an algorithm used to calculate gradients in neural networks.
A) True
B) False
4. What is the purpose of using gradient descent?
A) Optimization parameters
B) Prediction results (forward calculation in neural network)
C) Changing the model structure
D) Finding label values
5. Which of the following options is not a method in the development of natural language processing?
A) Rule-based approach
B) Statistical-based methods
C) Deep Learning-Based Methods
D) Recursion-based methods
Solutions:
| Question # 1 Answer: B,C,D | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: D |
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