When a model is trained on one task and the learned features are used as a starting point for a model on a second task, it's known as ________.
- Transfer Learning
- Data Augmentation
- Ensemble Learning
- Gradient Boosting
Transfer learning is a technique where knowledge gained from one task is applied as the starting point for another task. This helps leverage pre-trained models and speeds up learning on the new task.
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