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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 standard normal distribution are true?

A) The mean is 0.
B) The variance is 1.
C) The variance is 0.
D) The mean is 1.

2. Which of the following is not an acoustic feature of speech?

A) Semantics
B) Frequency
C) Duration
D) Amplitude

3. 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:

4. 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

5. In NLP tasks, transformer models perform well in multiple tasks due to their self-attention mechanism and parallel computing capability. Which of the following statements about transformer models are true?

A) A transformer model directly captures the dependency between different positions in the input sequence through the self-attention mechanism, without using the recurrent neural network (RNN) or convolutional neural network (CNN).
B) Transformer models outperform RNN and CNN in processing long texts because they can effectively capture global dependencies.
C) Multi-head attention is the core component of a transformer model. It computes multiple attention heads in parallel to capture semantic information in different subspaces.
D) Positional encoding is optional in a transformer model because the self-attention mechanism can naturally process the order information of sequences.

Solutions: