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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: Overview of ModelArts | 4% | - Development and deployment workflow - ModelArts platform architecture |
| Topic 3: 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 4: Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Topic 5: Theoretical Knowledge and Applications of Speech Processing | 10% | - Acoustic and language models - Speech processing basics - Speech recognition and synthesis |
| Topic 6: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - NLP core concepts - Text processing and representation - Common NLP tasks and applications |
| Topic 7: Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Topic 8: Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Topic 9: Neural Network Basics | 4% | - Artificial neural network principles - Network training and optimization - Deep learning fundamentals |
| Topic 10: ModelArts Platform Development Experiment | 10% |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
Question #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
Question #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 .()
Question #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.
Question #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
Question #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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