Transfer Learning
Expanded definition
Transfer learning leverages knowledge gained while solving one problem and applies it to a different but related problem. This approach is particularly useful when there is limited labeled data for the target task. By fine-tuning a pre-trained model on a new dataset, it can achieve high performance with less training time and resources. Transfer learning is widely used in natural language processing and computer vision, where large-scale models can be adapted to specific tasks.
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Transfer Learning FAQ
What is Transfer Learning?
A machine learning technique where a model developed for one task is reused for a different but related task.
How is Transfer Learning used in AI systems?
Transfer learning leverages knowledge gained while solving one problem and applies it to a different but related problem. This approach is particularly useful when there is limited labeled data for the target task. By fine-tuning a pre-trained model on a new dataset, it can achieve high performance with less training time and resources.
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