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

1. John wants to deploy a large model locally to implement the Q&A assistant function for his company. Which of the following factors is unnecessary for John to consider?

A) Output delay
B) Model security
C) Demand for computing power
D) Model development framework

2. The mAP evaluation metric in object detection combines accuracy and recall.

A) FALSE
B) TRUE

3. Which of the following statements about the multi-head attention mechanism of the Transformer are true?

A) The concatenated output is fed directly into the multi-headed attention mechanism.
B) Each header's query, key, and value undergo a shared linear transformation to obtain them.
C) The dimension for each header is calculated by dividing the original embedded dimension by the number of headers before concatenation.
D) The multi-head attention mechanism captures information about different subspaces within a sequence.

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

A) FALSE
B) TRUE

5. Which of the following statements about the functions of layer normalization and residual connection in the Transformer is true?

A) Residual connections and layer normalization help prevent vanishing gradients and exploding gradients in deep networks.
B) Residual connections primarily add depth to the model but do not aid in gradient propagation.
C) In shallow networks, residual connections are beneficial, but they aggravate the vanishing gradient problem in deep networks.
D) Layer normalization accelerates model convergence and does not affect model stability.

Solutions: