Practice Fully Connected Layer (fc) (23.4.5) - Convolutional Neural Network (CNN)

Practice: Fully Connected Layer (FC)

Lesson 23.4.5Convolutional Neural Network (CNN)

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9 questions

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6 sample questions

Question 1.
What is the main purpose of a Fully Connected Layer in a CNN?
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Think about the last step before a prediction is made.
Question 2.
Explain what a weighted sum is in the context of the FC layer.
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Consider how features influence the final decision.
3Question 3.
What is the role of the Fully Connected Layer in CNNs?
- To extract features
- To connect neurons
- To classify outputs
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It’s the last step before making predictions.
4Question 4.
True or False: The Softmax function is used in the Fully Connected Layer to compute probabilities.
- True
- False
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Think about how probabilities are derived for classification.
Question 5.
How would you modify a Fully Connected Layer to reduce the risk of overfitting in a CNN?
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Think about methods that help in generalizing the model rather than memorizing.
Question 6.
Consider a scenario where you have a significantly large feature vector in your FC layer. How might that impact computation, and what strategies could you employ to manage it?
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Consider how complexity affects processing.

5 more questions in this section. Enroll free to practise them all.