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Related Questions
- What are the benefits of using dropout regularization in deep neural networks?
- How does L1 and L2 regularization differ in terms of their effect on model complexity?
- What is the purpose of early stopping in training neural networks, and how does it prevent overfitting?
- Can you explain the concept of data augmentation and its role in improving model generalization?
- How does batch normalization help stabilize the training process and improve model performance?
- What is the difference between weight decay and dropout regularization, and when to use each?
- How can we use ensemble methods, such as bagging and boosting, to improve model generalization and reduce overfitting?
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