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Related Questions
- What are the primary differences between dropout and L1/L2 regularization in neural networks?
- How does dropout impact the model's ability to generalize to unseen data?
- Can you explain the concept of 'overfitting' and how dropout helps mitigate it?
- How does the dropout rate affect the model's performance on noisy or missing data?
- What are some common use cases where dropout is particularly effective?
- Can you describe the relationship between dropout and model capacity?
- How does dropout interact with other regularization techniques, such as weight decay?
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