Affiliation:
1. Department of Computer, College of Education, AL-Iraqia University, Baghdad, Iraq.
2. Department of Computer, College of Education, AL-Iraqia University, Iraq
3. Open AI L.L.C., 3180 18th Street, San Francisco, CA 94110, United States.
Abstract
Transfer Learning[1] is a machine learning technique that involves utilizing knowledge learned from one task to improve performance on another related task. This approach has been widely adopted in various fields such as computer vision, natural language processing, and speech recognition. The goal of this paper is to provide an overview of transfer learning and its recent developments. Transfer learning is particularly useful in situations where there is limited labeled data available for the target task. In these cases, the model can leverage knowledge learned from a related task with a larger amount of labeled data. This allows the model to overcome the problem of overfitting and improve performance on the target task.
Publisher
Mesopotamian Academic Press
Subject
Ocean Engineering,General Medicine,General Earth and Planetary Sciences,Earth and Planetary Sciences (miscellaneous),General Engineering,General Environmental Science,Geotechnical Engineering and Engineering Geology,General Earth and Planetary Sciences,General Environmental Science,Geometry and Topology,Algebra and Number Theory,Analysis,Geometry and Topology,Algebra and Number Theory,Analysis,General Agricultural and Biological Sciences,General Earth and Planetary Sciences,General Engineering,General Environmental Science
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