Transfer Learning
Transfer learning reuses pretrained models or features to speed up learning on new tasks with limited data. Techniques include fine-tuning, feature extraction, and adapters to trade off performance and compute cost.
Transfer learning reuses pretrained models or features to speed up learning on new tasks with limited data. Techniques include fine-tuning, feature extraction, and adapters to trade off performance and compute cost.