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Huawei H13-321_V2.5 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Deep Learning Fundamentals | 15% | - Training and Fine-tuning - Optimization Algorithms - CNN and RNN Architectures - Neural Network Basics |
| Topic 2: ModelArts Pro Development | 20% | - AutoML and Automatic Model Training - Model Deployment and Management - Inference Service Configuration - Hyperparameter Optimization |
| Topic 3: Image Recognition Application Development | 15% | - Object Detection Implementation - Image Segmentation - Transfer Learning with Pre-trained Models - Image Classification Models |
| Topic 4: HiLens Platform Development | 20% | - Multi-modal Data Processing - Skill Development Framework - Real-time Inference Optimization - Edge Deployment Strategy |
| Topic 5: Natural Language Processing Application | 15% | - Text Classification Models - Text Preprocessing and Embedding - Named Entity Recognition - Language Model Fine-tuning |
| Topic 6: EI Model Development Fundamentals | 15% | - EI Service and Architecture - Model Development Process - HiLens Framework and Skills - Development Environment Setup |
Huawei HCIP-AI-EI Developer V2.5 Sample Questions:
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:
Correct Answer:
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
In the field of deep learning, which of the following activation functions has a derivative not greater than 0.5?
- A. Tanh
- B. Sigmoid
- C. SeLU
- D. ReLU
Correct Answer: B 🗳️
Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).
The accuracy of object location detection can be evaluated using the intersection over union (IoU) value, which is a ratio. The denominator is the overlapping area between the prediction bounding box and ground truth bounding box, and the numerator is the area of union encompassed by both boxes.
- A. FALSE
- B. TRUE
Correct Answer: A 🗳️
Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).
In an HSV color space, H is for hue, S is for saturation, and V is for value. Which of the following statements about the HSV color space are true?
- A. Hue indicates the basic color attributes, such as red, green, and blue.
- B. Value is a measure of brightness. The image brightness can be enhanced by processing the V component of the HSV color space.
- C. The HSV color space perceives colors differently from human eyes, so it is not suitable for image segmentation or color analysis.
- D. Saturation describes how vivid the color is. The lower the saturation, the closer the color is to gray. The higher the saturation, the more vivid the color.
Correct Answer: A,B,D 🗳️
Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).
The natural language processing field usually uses distributed semantic representation to represent words.
Each word is no longer a completely orthogonal 0-1 vector, but a point in a multi-dimensional real number space, which is specifically represented as a real number vector.
- A. FALSE
- B. TRUE
Correct Answer: B 🗳️
Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).
