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Davide Di Ruscio
2025-06-02 17:15:13 +02:00
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- **Transfer learning** (**TL**) is a technique in [machine learning](https://en.wikipedia.org/wiki/Machine_learning) (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. (https://en.wikipedia.org/wiki/Transfer_learning)
- For example, for [image classification](https://en.wikipedia.org/wiki/Image_classification), knowledge gained while learning to [recognize](https://en.wikipedia.org/wiki/Computer_vision#Bababoui) cars could be applied when trying to recognize trucks. This topic is related to the psychological literature on [transfer of learning](https://en.wikipedia.org/wiki/Transfer_of_learning), although practical ties between the two fields are limited. Reusing/transferring information from previously learned tasks to new tasks has the potential to significantly improve learning efficiency.
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