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

1. The U-Net uses an upsampling mechanism and has a fully-connected layer.

A) TRUE
B) FALSE

2. The deep neural network (DNN)-hidden Markov model (HMM) does not require the HMM-Gaussian mixture model (GMM) as an auxiliary.

A) TRUE
B) FALSE

3. -------- is a text representation method based on the bag of words (BoW) model. It decomposes words into subwords and then adds the vector representations of the subwords to obtain word vectors, fully utilizing character N-gram information. (Fill in the blank.)

4. How many parameters need to be learned when a 3 × 3 convolution kernel is used to perform the convolution operation on two three-channel color images?

A) 10
B) 55
C) 28
D) 9

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

Solutions: