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Huawei H13-321_V2.5 valid - in .pdf
- Exam Code: H13-321_V2.5
- Exam Name: HCIP-AI-EI Developer V2.5
- Q & A: 62 Questions and Answers
- PDF Price: $59.99
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- Exam Code: H13-321_V2.5
- Exam Name: HCIP-AI-EI Developer V2.5
- Q & A: 62 Questions and Answers
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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Overview of Huawei's AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | - All-scenario AI solutions - Full-stack AI technology system - Huawei AI development layout |
| Topic 2: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Practical application - Machine translation, text generation and other technologies - Text processing and representation - Language model and semantic understanding |
| Topic 3: Neural Network Basics | 4% | - Training and optimization methods - Basic concepts of neural networks - Common neural network structures |
| Topic 4: Image Processing Lab Guide | 12% | - Performance optimization and testing - Development environment setup - Image processing model development and deployment |
| Topic 5: Theoretical Knowledge and Applications of Speech Processing | 10% | - Application cases - Speech feature extraction - Speech signal processing foundation - Speech recognition and synthesis |
| Topic 6: Theoretical Knowledge and Applications of Image Processing | 26% | - Image classification, detection and segmentation - Image preprocessing technology - Typical application scenarios - Feature extraction and representation |
| Topic 7: Overview of ModelArts | 4% | - Core functions and service modules - Basic operation process - ModelArts positioning and architecture |
| Topic 8: Speech Processing Lab Guide | 12% | - Speech model building and tuning - Application deployment and verification - Speech data processing practice |
| Topic 9: Natural Language Processing Lab Guide | 10% | - NLP model training and evaluation - End-to-end application development - Text preprocessing and feature engineering |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
1. Mel-frequency cepstral coefficients (MFCCs) take into account human auditory characteristics by first mapping the linear spectrum to the Mel nonlinear spectrum based on auditory perception, and then converting it to the cepstral domain.
A) TRUE
B) FALSE
2. What are the adjacency relationships between two pixels whose coordinates are (21,13) and (22,12)?
A) Diagonal adjacency
B) No adjacency relationship
C) 8-adjacency
D) 4-adjacency
3. What type of task is viewed when using the Seq2Seq model in speech recognition?
A) Classification task
B) Regression task
C) Clustering task
D) Dimensionality reduction task
4. In cases where the bright and dark areas of an image are too extreme, which of the following techniques can be used to improve the image?
A) Inversion
B) Gamma correction
C) Grayscale compression
D) Grayscale stretching
5. 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) TRUE
B) FALSE
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A,C | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |
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