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Related Questions
- What is the primary purpose of batch normalization in deep learning models, particularly when using transfer learning?
- How does batch normalization help prevent overfitting in models that have been pre-trained using transfer learning?
- Can you explain the difference between batch normalization and instance normalization, and when to use each?
- How does batch normalization affect the training process of a model, and what are its implications for convergence?
- Is batch normalization typically applied to the output of each layer, or only to certain layers, and why?
- What are the common challenges associated with batch normalization, and how can they be addressed?
- Can you provide an example of a scenario where batch normalization is particularly useful when using transfer learning?
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