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Description
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Feature Description
Transfer Learning is a machine learning technique where a model developed for a particular task is reused as the starting point for a model on a second task. This approach leverages the knowledge gained from the first task to improve the learning efficiency and performance on the new task, especially when the new task has limited labeled data.
Use Case
In a real-time use case, a researcher working on medical image analysis for detecting tumors can use a pre-trained model on general image recognition. By fine-tuning this model with a smaller set of medical images, the researcher can achieve high accuracy in tumor detection more quickly and with less data than training a model from scratch.
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Priority
High
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