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Huawei H13-321_V2.5 Exam Syllabus Topics:

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

1. In natural language processing tasks, word vector evaluation is an important aspect for measuring the performance of a word embedding model. Which of the following statements about word vector evaluation are true?

A) Word vector evaluation can be performed through intrinsic evaluation. Common methods include word similarity tasks and word analogy tasks.
B) Extrinsic evaluation is the main method used for evaluating word vectors because it directly reflects the performance of word vectors in real-world application tasks.
C) The word analogy task evaluates the capability of word vectors in capturing semantic relationships between words, for example, by determining whether "king - man + woman = ?" is close to "queen".
D) Word similarity tasks typically employ manually labeled datasets to evaluate word vectors, compute the cosine similarity between word vectors, and compare it with the manual labeling result.

2. The development of large models should comply with ethical principles to ensure the legal, fair, and transparent use of data.

A) FALSE
B) TRUE

3. 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) Positional encoding is optional in a transformer model because the self-attention mechanism can naturally process the order information of sequences.
B) 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).
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) Transformer models outperform RNN and CNN in processing long texts because they can effectively capture global dependencies.

4. Which of the following are object detection algorithms?

A) R-CNN
B) SSD
C) Faster-R-CNN
D) YOLO

5. Maximum likelihood estimation (MLE) can be used for parameter estimation in a Gaussian mixture model (GMM).

A) FALSE
B) TRUE

Solutions: