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[General] Practice Huawei H13-321_V2.5 Mock - H13-321_V2.5 Reliable Exam Tips

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【General】 Practice Huawei H13-321_V2.5 Mock - H13-321_V2.5 Reliable Exam Tips

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Huawei HCIP-AI-EI Developer V2.5 Sample Questions (Q56-Q61):NEW QUESTION # 56
Which of the following statements about the standard normal distribution are true?
  • A. The variance is 0.
  • B. The variance is 1.
  • C. The mean is 0.
  • D. The mean is 1.
Answer: B,C
Explanation:
Astandard normal distributionis a special case of the normal distribution with:
* Mean (#) = 0
* Variance (#²) = 1This standardization is widely used in statistics and machine learning to normalize features for improved model convergence. Statements A and B are incorrect because variance is never 0 in a valid distribution, and the mean is 0, not 1.
Exact Extract from HCIP-AI EI Developer V2.5:
"The standard normal distribution is defined with # = 0 and #² = 1, providing a normalized scale for statistical analysis." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Probability and Statistics Fundamentals

NEW QUESTION # 57
When the chi-square test is used for feature selection, SelectKBest and _____ function or class must be imported from the sklearn.feature_selection module. (Enter the function interface name.) chi2 Explanation:
In feature selection for classification tasks, thechi-square (#²)statistical test can be applied to evaluate the independence between features and target labels.
In Python's scikit-learn library, this is implemented using:
Answer:
Explanation:
python
CopyEdit
from sklearn.feature_selection import SelectKBest, chi2
SelectKBest selects the top K features based on scores returned by the chi2 function.
Exact Extract from HCIP-AI EI Developer V2.5:
"In scikit-learn, SelectKBest with chi2 can be used for feature selection by scoring features according to the chi-square statistic." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Feature Selection Methods

NEW QUESTION # 58
Which of the following are object detection algorithms?
  • A. R-CNN
  • B. YOLO
  • C. SSD
  • D. Faster-R-CNN
Answer: A,B,C,D
Explanation:
The major families of object detection algorithms include:
* R-CNN (Region-based CNN):Uses region proposals with CNN feature extraction.
* YOLO (You Only Look Once)erforms real-time detection by predicting bounding boxes and class probabilities in a single pass.
* SSD (Single Shot MultiBox Detector):Uses multiple feature maps for detecting objects at different scales in one pass.
* Faster-R-CNN:Improves R-CNN with a Region Proposal Network for speed.
Exact Extract from HCIP-AI EI Developer V2.5:
"Common object detection algorithms include R-CNN, Faster R-CNN, YOLO, and SSD, each using different approaches for balancing accuracy and speed." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Object Detection

NEW QUESTION # 59
Which of the following applications are supported by ModelArts ExeML?
  • A. Dress code conformance monitoring in campuses
  • B. Anomalous sound detection in production or security scenarios
  • C. Automatic offering classification
  • D. Predictive maintenance of manufacturing equipment
Answer: A,B,C,D
Explanation:
ModelArtsExeML(Expert Experience Machine Learning) enables users without programming expertise to build AI models through a visual interface. It supports multiple application scenarios, including:
* Predictive maintenance in manufacturing to detect potential equipment failures.
* Monitoring compliance with dress codes in school or workplace settings.
* Detecting unusual sounds in manufacturing or security contexts.
* Classifying offerings automatically in e-commerce or retail systems.
Exact Extract from HCIP-AI EI Developer V2.5:
"ModelArts ExeML supports intelligent applications in industrial maintenance, campus security, sound anomaly detection, and automated product classification." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: ModelArts ExeML Application Scenarios

NEW QUESTION # 60
In the field of deep learning, which of the following activation functions has a derivative not greater than 0.5?
  • A. Sigmoid
  • B. SeLU
  • C. Tanh
  • D. ReLU
Answer: A
Explanation:
Thesigmoidactivation function maps inputs to the range (0, 1) and has a maximum derivative of 0.25 at x=0.
This derivative value is always # 0.5, making it the correct choice here. While sigmoid is historically used in neural networks, it suffers from the vanishing gradient problem for large positive or negative inputs due to its small derivative values. Other functions such as ReLU, Tanh, and SeLU have different derivative behaviors, with ReLU having a derivative of 1 for positive inputs, Tanh having derivatives up to 1, and SeLU designed for self-normalizing networks with derivatives potentially greater than 0.5.
Exact Extract from HCIP-AI EI Developer V2.5:
"Sigmoid compresses values into the (0,1) range, with its maximum derivative being 0.25, which is always less than 0.5." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Activation Functions in Neural Networks

NEW QUESTION # 61
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