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Discover LudwigThe phrase "transfer learning" is correct and usable in written English.
Transfer learning is a type of machine learning technique where knowledge gained from one problem is applied to a different but related problem. For example, a machine learning algorithm trained to identify cats in images could be used to identify dogs in images by using the knowledge gained in the previous problem.
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A survey on transfer learning.
Towards speeding audio EQ interface building with transfer learning.
Transfusion: Understanding Transfer Learning with Applications to Medical Imaging.
Weiss, K., Khoshgoftaar, T.M. & Wang, D. A survey of transfer learning.
To overcome these problems we introduce a novel transfer learning approach.
"Transfer learning application" section provides examples of transfer learning applications.
Detailed information on specific transfer learning solutions are presented in "Homogeneous transfer learning" "Heterogeneous transfer learning" and "Negative transfer" sections.
This can be achieved using transfer learning.
Equation (1) is modified for transfer learning.
"Homogeneous transfer learning" "Heterogeneous transfer learning" and "Negative transfer" sections cover homogeneous transfer learning solutions, heterogeneous transfer learning solutions, and solutions addressing negative transfer, respectively.
This is the motivation for transfer learning.
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