Huawei HCIP-AI EI Developer H13-321_V2.5

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

1. Seq2Seq is a model that translates one sequence into another sequence, essentially consisting of two recurrent neural networks (RNNs), one is the Encoder, and the other is the ---------. (Fill in the blank.)

2. Among image preprocessing techniques, gamma correction is a common non-linear brightness adjustment method. Which of the following statements are true about the application and features of gamma correction?

A) Gamma correction applies only to grayscale images and does not apply to color images.
B) When # < 1, the input high grayscale range is compressed, and the low grayscale range is stretched, enhancing the dark areas while compressing the bright areas.
C) Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.
D) When # > 1, the input low grayscale range is compressed, and the high grayscale range is stretched, enhancing the bright areas while compressing the dark areas.

3. Which of the following is a learning algorithm used for Markov chains?

A) Baum-Welch algorithm
B) Exhaustive search
C) Viterbi algorithm
D) Forward-backward algorithm

4. The attention mechanism in foundation model architectures allows the model to focus on specific parts of the input data. Which of the following steps are key components of a standard attention mechanism?

A) Normalize the attention scores to obtain attention weights.
B) Calculate the dot product similarity between the query and key vectors to obtain attention scores.
C) Apply a non-linear mapping to the result obtained after the weighted summation.
D) Compute the weighted sum of the value vectors using the attention weights.

5. Which of the following statements about the functions of the encoder and decoder is true?

A) The encoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.
B) The output lengths of the encoder and decoder are the same.
C) The decoder converts variable-length input sequences into fixed-length context vectors, encoding the information of the input sequences in the context vectors.
D) The encoder converts context vectors into variable-length output sequences.

Solutions: