Practice Introduction (23.1) - Convolutional Neural Network (CNN)

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6 sample questions

Question 1.
What does CNN stand for?
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Think about what relates to images and networks!
Question 2.
Name one application of CNNs.
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What can you unlock with your face?
3Question 3.
What does CNN stand for?
- Convolutional Neural Network
- Comprehensive Neural Network
- Computation Neural Node
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Remember what is critical for visual data.
4Question 4.
True or False: CNNs require manual features to be extracted for image processing.
- True
- False
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Think about how machines learn from images.
Question 5.
Explain the advantages CNNs have over traditional neural networks in image processing, citing specific examples.
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Reflect on image data vs. text data.
Question 6.
Design a basic example of how a CNN identifies a feature in an image. Describe the layers involved.
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Think about the steps layers of the CNN follow.

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