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Evaluation of machine learning approaches for transfer learning

Transfer learning is becoming a popular machine learning approach which aims to transfer knowledge from a source domain to a target domain. Domain adaptation is a special case of transfer learning. Domain adaptation has proven to be significant in classification tasks where the target domain does not have labelled data, a requirement for building classifiers, however, there exists a related labelled data, called as source domain.Domain adaptation has been studied in the recent time and hence there exists many variants …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

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