This exam you need to understand the meaning of the H13-321_V2.0-ENU questions,because when you have the real test,the questions optionorder will change,even the answers will change.

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| Section | Weight | Objectives |
|---|---|---|
| Theoretical Knowledge and Applications of Speech Processing | 10% | - Speech recognition and synthesis - Acoustic and language models - Speech processing basics |
| Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Overview of ModelArts | 4% | - Development and deployment workflow - ModelArts platform architecture |
| Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Text processing and representation - Common NLP tasks and applications - NLP core concepts |
| ModelArts Platform Development Experiment | 10% | |
| Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | |
| Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Theoretical Knowledge and Applications of Image Processing | 26% | - Image preprocessing and feature extraction - Computer vision overview - Convolutional neural networks - Image recognition, detection and segmentation |
| Neural Network Basics | 4% | - Network training and optimization - Deep learning fundamentals - Artificial neural network principles |
Question 1
Deep learning model training requires a large amount of data. In actual operation, random noise can be added to the training image data set through data enhancement technology to expand the sample size of the data set.
A. False
B. True
Question 2
cv2.LUT (img, trans_table) function means using OpenCV's look up table function to modify the grayscale value of the image.
A. False
B. True
Question 3
Syntactic analysis generally uses a syntax tree to represent the analysis results.
A. False
B. True
Question 4
What is the main function of the convolution kernel?
A. Extracting local features
B. Color Enhancement
C. Dimensionality reduction
D. Change image size
Question 5
Language models can be used to solve problems such as predicting the next word based on context.
A. False
B. True
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: A | Question 5 Answer: B |
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