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RedHat Red Hat Certified Specialist in Containers Sample Questions:

1. Which of the following statements about the sigmoid function is correct? (Multiple choice)

A) 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.
B) Sigmoid output is not centered on 0
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

2. What is Huawei's self- developed deep learning framework?

3. What is the output of graphical analysis?

A) Image Content
B) Image pixel value (no need to analyze, can be directly retrieved)
C) Image size (no need to analyze, can be directly retrieved)
D) Image grayscale value (no need to analyze, can be directly retrieved)

4. How do you tag an image with a new name in Podman?

A) podman update <old> <new>
B) podman rename <old> <new>
C) podman tag <old> <new>
D) podman reimage <old> <new>

5. The core problem of computer vision ()

Solutions: