What is transfer learning, and when would you use it?
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Answer / Dharmendra Kumar
Transfer learning involves using a pre-trained model as a starting point for a new task. This can save time and resources, as the model already has learned features from a large dataset related to the original task. Transfer learning is useful when there are limited amounts of labeled data available for the new task or when the new task is similar to an existing one.
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