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Related Questions
- What are the benefits and drawbacks of pre-training neural networks before fine-tuning them on specific tasks?
- How can transfer learning help to avoid overfitting and underfitting in machine learning models?
- What are some examples of tasks where transfer learning can improve the generalizability of machine learning models, such as natural language processing or computer vision?
- How can knowledge distillation and meta-learning be used to further enhance the generalizability of transfer learning models?
- What are the implications of transfer learning for self-supervised learning and lifelong learning?
- Can transfer learning be applied to explainable AI to improve the transparency and fairness of machine learning models?
- What role does data augmentation play in improving the generalizability of transfer learning models by reducing the reliance on small datasets?
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