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[General] H13-321_V2.5 Frequent Updates | Reliable H13-321_V2.5 Braindumps Pdf

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【General】 H13-321_V2.5 Frequent Updates | Reliable H13-321_V2.5 Braindumps Pdf

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Huawei HCIP-AI-EI Developer V2.5 Sample Questions (Q17-Q22):NEW QUESTION # 17
Huawei Cloud ModelArts is a one-stop AI development platform that supports multiple AI scenarios. Which of the following scenarios are supported by ModelArts?
  • A. Speech recognition
  • B. Image classification
  • C. Object detection
  • D. Video analytics
Answer: A,B,C,D
Explanation:
ModelArts provides an integrated environment for data labeling, model training, deployment, and management, supporting various AI application scenarios:
* Image classificationfor categorizing visual content.
* Object detectionfor locating and identifying multiple objects in images or video frames.
* Speech recognitionfor converting speech to text.
* Video analyticsfor automated video content analysis.
Exact Extract from HCIP-AI EI Developer V2.5:
"ModelArts supports a wide range of AI tasks including image classification, object detection, speech recognition, and intelligent video analytics." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: ModelArts Overview

NEW QUESTION # 18
The image saturation can be enhanced by processing the ________ component of the HSV color space. (Enter H, S, or V.)
Answer:
Explanation:
S
Explanation:
In the HSV (Hue, Saturation, Value) color model:
* Hrepresents hue (color type).
* Srepresents saturation (color intensity or vividness).
* Vrepresents brightness.
To enhance saturation in an image, adjustments are made to theS component. Increasing S increases the color vividness, making the image appear more vibrant, while reducing S moves colors toward grayscale. This approach is widely used in image enhancement tasks, especially in object recognition and segmentation, where vivid colors improve feature contrast.
Exact Extract from HCIP-AI EI Developer V2.5:
"In HSV color space, saturation (S) describes the vividness of colors. Increasing the S value enhances saturation, making colors more intense, while decreasing it makes them closer to gray." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Image Processing Basics

NEW QUESTION # 19
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.
Answer: A,B,D
Explanation:
The standardattention mechanisminvolves:
* Computing attention scores via the dot product of query and key vectors (A).
* Applying a normalization function (typically softmax) to obtain attention weights (D).
* Using these weights to compute a weighted sum of the value vectors (B).OptionCis not a standard step
- non-linear mappings are not applied after the weighted sum in the basic attention formula.
Exact Extract from HCIP-AI EI Developer V2.5:
"Attention computes dot products between query and key, normalizes scores with softmax, and uses them to weight value vectors." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Attention Mechanism Fundamentals

NEW QUESTION # 20
-------- is a text representation method based on the bag of words (BoW) model. It decomposes words into subwords and then adds the vector representations of the subwords to obtain word vectors, fully utilizing character N-gram information. (Fill in the blank.)
Answer:
Explanation:
FastText
Explanation:
FastTextis an extension of Word2Vec developed by Facebook AI Research. Unlike Word2Vec, which learns embeddings for whole words, FastText represents each word as a sum of its character n-gram embeddings.
This helps in handling rare words and morphologically rich languages by generating embeddings for unseen words from their subword components.
Exact Extract from HCIP-AI EI Developer V2.5:
"FastText decomposes words into character n-grams and represents words as the sum of their n-gram vectors, improving representation for rare and out-of-vocabulary words." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Subword Embedding Models

NEW QUESTION # 21
The development of large models should comply with ethical principles to ensure the legal, fair, and transparent use of data.
  • A. FALSE
  • B. TRUE
Answer: B
Explanation:
Ethical AI development requires ensuring that large models are trained and deployed in a way that respects laws, fairness, and transparency. This includes preventing bias, ensuring user privacy, protecting intellectual property, and being transparent about data usage and decision-making processes.
Exact Extract from HCIP-AI EI Developer V2.5:
"The development and deployment of large models must follow ethical principles to ensure legal, fair, and transparent use of data, avoiding bias and misuse." Reference:HCIP-AI EI Developer V2.5 Official Study Guide - Chapter: Ethical AI Practices

NEW QUESTION # 22
......
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