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| Section | Weight | Objectives |
|---|---|---|
| Natural Language Processing Lab Guide | 10% | |
| Overview of Huawei's AI Development Strategy and Full-Stack All-Scenario AI Portfolio | 2% | |
| Natural Language Processing Theory and Applications | 10% | |
| Overview of ModelArts | 4% | |
| Neural Network Basics | 4% | |
| Image Processing Lab Guide | 12% | |
| Image Processing Theory and Applications | 26% | |
| Speech Processing Lab Guide | 12% | |
| ModelArts Lab Guide | 10% | |
| Speech Processing Theory and Applications | 10% |
1. What are the evaluation indicators used in image segmentation?
2. The lower the value on the diagonal of the confusion matrix, the better the classification effect of the classifier.
A) True
B) False
3. Which algorithm engines does ModelArts training job support? (Multiple choice)
A) PyTorch
B) XGBoost
C) TensorFlow
D) MXNet
4. Which of the following options does not belong to the category of phonetics?
A) Linguistic Phonetics
B) Semantic Phonetics
C) Auditory Phonetics
D) Articulation and Phonetics
E) Acoustic Phonetics
5. Which of the following statements about the sigmoid function is correct? (Multiple choice)
A) Sigmoid output is not centered on 0
B) Generally speaking, within 5 layers of Sigmoid network, the gradient will degenerate to 0, making it difficult to train. This phenomenon is called the vanishing gradient phenomenon.
C) Sigmoid function is monotonous and continuous, easy to derive, bounded output, and the network is easy to converge.
D) When the network is very deep, the modulus of the gradient becomes smaller and smaller
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: B | Question # 3 Answer: A,B,C | Question # 4 Answer: B | Question # 5 Answer: B,C,D |
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