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Learn why transfer learning is crucial for deep learning and how it reduces training time and data requirements.
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Transfer learning reduces training time and data requirements.
Transfer learning is a technique where a pre-trained model is fine-tuned for a new task, reducing the need for large datasets and training time.
Why transfer learning matters for deep learning.
1. Reduces training time. 2. Requires less data. 3. Improves model performance. 4. Cost-effective.
Steps to understand transfer learning.
1. Select a pre-trained model. 2. Fine-tune the model for the new task. 3. Evaluate and deploy the model.
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