What is transfer learning?Disscuss the factor affecting transfer of learning?
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Transfer learning is a research problem in machine learning that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.[1] For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks. This area of research bears some relation to the long history of psychological literature on transfer of learning, although formal ties between the two fields are limited.
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Transfer is understood as to the degree by which the participants apply the knowledge, abilities and attitudes required in a specific working context (Baldwin & Ford, 1988). In Olsen's words (1998) “transfer is the evidence that what was learned is actually being used on the job for which it was intended” (p.
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