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  2. Transfer of learning - Wikipedia

    en.wikipedia.org/wiki/Transfer_of_learning

    Transfer is less a deliberate activity by the learner than it is a result of the environment at the time of learning. Teachers, being part of the learning environment, can be an instrument of transfer (both positive and negative). [ 7 ]

  3. Transfer learning - Wikipedia

    en.wikipedia.org/wiki/Transfer_learning

    Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification , knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.

  4. Everything you need to know about transfer learning in AI - AOL

    www.aol.com/everything-know-transfer-learning-ai...

    Unfortunately, when created from scratch, deep learning models require access to vast amounts of data and compute resources. Fortunately, transfer learning, the discipline of using the knowledge ...

  5. Knowledge transfer - Wikipedia

    en.wikipedia.org/wiki/Knowledge_transfer

    Knowledge transfer icon from The Noun Project. Knowledge transfer refers to transferring an awareness of facts or practical skills from one entity to another. [1] The particular profile of transfer processes activated for a given situation depends on (a) the type of knowledge to be transferred and how it is represented (the source and recipient relationship with this knowledge) and (b) the ...

  6. Learning theory (education) - Wikipedia

    en.wikipedia.org/wiki/Learning_theory_(education)

    An example of the hugging strategy is when a student practices teaching a lesson or when a student role plays with another student. These examples encourage critical thinking that engages the student and helps them understand what they are learning—one of the goals of transfer of learning [24] and desirable difficulties.

  7. Domain adaptation - Wikipedia

    en.wikipedia.org/wiki/Domain_Adaptation

    Domain adaptation is a specialized area within transfer learning. In domain adaptation, the source and target domains share the same feature space but differ in their data distributions. In contrast, transfer learning encompasses broader scenarios, including cases where the target domain’s feature space differs from that of the source domain ...

  8. Transfer-appropriate processing - Wikipedia

    en.wikipedia.org/wiki/Transfer-appropriate...

    Transfer-appropriate processing (TAP) is a type of state-dependent memory specifically showing that memory performance is not only determined by the depth of processing (where associating meaning with information strengthens the memory; see levels-of-processing effect), but by the relationship between how information is initially encoded and how it is later retrieved.

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