Practice Limitations Of Neural Networks (8.7) - Neural Network

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6 sample questions

Question 1.
What does 'data hungry' mean in the context of neural networks?
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Think about the food analogy.
Question 2.
Name one consequence of overfitting in a neural network.
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Think about how well it does on training versus new data.
3Question 3.
What does 'data hungry' refer to?
- A need for large amounts of unlabeled data
- Need for large amounts of labeled data
- A model that does not learn
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Think about data requirements.
4Question 4.
True or False: Neural networks can easily explain how they make their decisions.
- True
- False
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Think about interpretability.
Question 5.
Develop a strategy to improve a neural network model that is underperforming due to overfitting. Include specific techniques you would use and why.
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Consider ways to modify training practices and structures.
Question 6.
Discuss how the black box nature of neural networks can pose ethical challenges in applications like credit scoring. What approaches could be taken to alleviate these concerns?
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Think about responsibility and fairness in AI applications.

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