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Huawei H13-321_V2.0-ENU Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Speech Processing | 22% | - Speech Processing Theory and Applications - Speech Processing Lab Guide |
| Natural Language Processing (NLP) | 20% | - NLP Lab Guide - NLP Theory and Applications |
| AI Fundamentals and Neural Networks | 4% | - Neural Network Basics |
| Huawei AI Ecosystem and ModelArts | 16% | - ModelArts Platform Overview - ModelArts Lab Guide - Huawei AI Strategy and Ecosystem Overview |
| Computer Vision (Image Processing) | 26% | - Image Processing Theory and Applications
|
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
1. Which of the following can be done using Tensorboard? (Multiple choice)
A) Automatic parameter tuning (what the algorithm needs to do)
B) Visualize the changes in loss and accuracy during deep learning training
C) Data Annotation (Tensorboard is not an annotation tool)
D) Visualizing high-dimensional distributions
2. What will change in the image if the H component of the HSV color space is modified?
A) Brightness (V)
B) Hue (warmth or coldness of the image)
C) Contrast
D) Saturation (S)
3. What are the ways to initiate a REST API request?
4. In convolutional neural networks, convolutional layers can play a role in dimensionality reduction.
A) False
B) True
5. The model parameters of the hidden Markov model include sequence length, transition probability, initial probability and emission frequency.
A) False
B) True
Solutions:
| Question # 1 Answer: B,D | Question # 2 Answer: B | Question # 3 Answer: Only visible for members | Question # 4 Answer: B | Question # 5 Answer: A |
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