Huawei HCIP-AI-EI Developer V2.5 : H13-321_V2.5

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Huawei H13-321_V2.5 Exam Syllabus Topics:

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

Question 1

Which of the following methods are useful when tackling overfitting?

A. Using dropout during model training
B. Data augmentation
C. Using more complex models
D. Using parameter norm penalties

Question 2

Which of the following statements about the standard normal distribution are true?

A. The variance is 1.
B. The mean is 1.
C. The variance is 0.
D. The mean is 0.

Question 3

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

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

Question 4

Transformer models outperform LSTM when analyzing and processing long-distance dependencies, making them more effective for sequence data processing.

A. TRUE
B. FALSE

Question 5

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. 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.
D. Gamma correction is an enhancement technique based on exponential transformation mapping. It is used for non-linear contrast stretching.

Solutions: