Transfer Learning
A machine learning method where a model developed for a task is reused as the starting point for a model on a second task.
Description
Transfer Learning is a machine learning technique where knowledge gained while solving one problem is applied to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks. This approach is particularly valuable when the new task has limited training data.
Examples
- 🖼️ Using ImageNet pre-trained models for custom image classification
- 🔤 Fine-tuning BERT for specific NLP tasks
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