What is the main purpose of regularization techniques like dropout and L2 regularization in deep learning models?
- Reduce overfitting
- Increase model complexity
- Speed up training
- Improve convergence
Regularization techniques like dropout and L2 regularization are used to reduce overfitting by adding penalties for complex models and preventing overfitting of training data.
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