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Huawei H13-321_V2.5 Exam Syllabus Topics:

Huawei HCIP-AI-EI Developer V2.5 Sample Questions:

1. Which of the following statements about the functions of the encoder and decoder is true?

A) The encoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.
B) The encoder converts context vectors into variable-length output sequences.
C) The output lengths of the encoder and decoder are the same.
D) The decoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.

2. Which of the following are required for the image object detection algorithm?

A) Object classification determination
B) Object contour calculation
C) Object location calculation
D) Confidence calculation

3. Which of the following has never been used as a method in the history of NLP?

A) Rule-based method
B) Deep learning-based method
C) Recursion-based method
D) Statistics-based method

4. When the chi-square test is used for feature selection, SelectKBest and _____ function or class must be imported from the sklearn.feature_selection module. (Enter the function interface name.) chi2 Explanation:
In feature selection for classification tasks, thechi-square (#²)statistical test can be applied to evaluate the independence between features and target labels.
In Python's scikit-learn library, this is implemented using:

5. In the image recognition algorithm, the structure design of the convolutional layer has a great impact on its performance. Which of the following statements are true about the structure and mechanism of the convolutional layer? (Transposed convolution is not considered.)

A) The convolutional layer slides over the input feature map using a convolution kernel of a fixed size to extract local features without explicitly defining their features.
B) A stride in the convolutional layer can control the spatial resolution of the output feature map. A larger stride indicates a smaller output feature map and simpler calculation.
C) In the convolutional layer, each neuron only collects some information. This effectively reduces the memory required.
D) The convolutional layer uses parameter sharing so that features at different positions share the same group of parameters. This reduces the number of network parameters required but reduces the expression capabilities of models.

Solutions: