Practice Challenges In Training (8.3.3) - Deep Learning and Neural Networks

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11 questions

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4 cards from this section. Quick, good the night before a test.
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6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
5 questions · about 3 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is the vanishing gradient problem?
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Think about how gradients affect learning.
Question 2.
List one strategy to mitigate overfitting.
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Think about regularization techniques.
3Question 3.
What happens during the vanishing gradient problem?
- Gradients become too small
- Gradients become too large
- Gradients are unaffected
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Remember how gradients affect learning.
4Question 4.
True or False: Overfitting leads to poor performance on training data.
- True
- False
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Consider the meaning of overfitting.
Question 5.
Design an experiment to measure the impact of dropout on a network's performance. What metrics will you use?
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Consider practical metrics that reflect training success.
Question 6.
Discuss how computational complexity in deep learning might evolve with advancements in hardware technology. What could the future hold?
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Think about trends in technology and their implications.

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