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Transfer Learning
Transfer learning is a machine learning technique where a model trained for one task is repurposed as a starting point for a different, but related, task. Instead of training a new model from scratch, the pre-trained model's learned features and weights are adapted, significantly reducing training time and data requirements for the new task.
In plain terms
Transfer learning is like learning to ride a unicycle after you've already mastered riding a bicycle, leveraging existing skills for a new challenge.
Why it matters
It drastically accelerates model development and enables high-performing AI even with limited datasets, democratizing access to advanced AI capabilities.
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