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Huawei H13-321_V2.5 Exam Syllabus Topics:

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

Question 1

In 2017, the Google machine translation team proposed the Transformer in their paperAttention is All You Need. The Transformer consists of an encoder and a(n) --------. (Fill in the blank.)

Question 2

What are the advantages of deep learning-based speech recognition algorithms?

A. End-to-end task processing
B. Forced alignment of annotated data
C. No data training
D. Automated feature extraction

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

Question 4

What type of task is viewed when using the Seq2Seq model in speech recognition?

A. Regression task
B. Classification task
C. Clustering task
D. Dimensionality reduction task

Question 5

------- is a model that uses a convolutional neural network (CNN) to classify texts.

Solutions: