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Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | |
| Topic 2: ModelArts Platform Development Experiment | 10% | |
| Topic 3: Neural Network Basics | 4% | - Artificial neural network principles - Network training and optimization - Deep learning fundamentals |
| Topic 4: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - NLP core concepts - Text processing and representation - Common NLP tasks and applications |
| Topic 5: Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Topic 6: Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Topic 7: Theoretical Knowledge and Applications of Speech Processing | 10% | - Acoustic and language models - Speech processing basics - Speech recognition and synthesis |
| Topic 8: Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Topic 9: Theoretical Knowledge and Applications of Image Processing | 26% | - Image preprocessing and feature extraction - Computer vision overview - Image recognition, detection and segmentation - Convolutional neural networks |
| Topic 10: Overview of ModelArts | 4% | - Development and deployment workflow - ModelArts platform architecture |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. The larger the template size, the better the denoising effect of the mean filter. When performing denoising, a large-sized template should be selected for mean filtering.
A) True
B) False
2. MoXing is a network model development API provided by Huawei Cloud ModelArts service. Using the mox.file module in MoXing , calling the API can directly access files in OBS. The operation commands correspond to the OS module in Python and the gfile module in TensorFlow. Among them, mox.file.remove (..., recursive=True) corresponds to shutil .()
3. Regarding CBOW and Skip-Gram algorithms, which of the following statements is incorrect?
A) Both the CBOW model and the skip-gram model are based on the Huffman tree.
B) Skip-Gram calculates the probabilities of several words before and after a certain word.
C) CBOW calculates the probability of a word appearing based on the n words preceding it or the n consecutive words before and after it.
D) Both CBOW and Skip-Gram can be used to train word embeddings, but Skip-Gram is faster than CBOW.
4. The larger the image sampling interval, the higher the spatial resolution of the image, and thus the better the image quality.
A) True
B) False
5. There are two main methods for semi-supervised learning: one is to perform unsupervised clustering first and then supervised learning. The other is Self-Learning.
A) True
B) False
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: Only visible for members | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: A |
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