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

1. 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.

2. Maximum likelihood estimation (MLE) requires knowledge of the sample data's distribution type.

A) TRUE
B) FALSE

3. Overfitting is a condition where a model is overly simple and excessive generalization errors occur.

A) TRUE
B) FALSE

4. Which of the following is not an algorithm for training word vectors?

A) FastText
B) Word2Vec
C) BERT
D) TextCNN

5. Which of the following ModelArts training parameters is used to customize hyperparameters?

A) Resource Pool
B) Compute Nodes
C) Hyperparameter
D) Algorithm Type

Solutions: