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One-Shot Learning

Background on "One-Shot Learning"

One-Shot Learning is a machine learning method where a model can learn and generalize from a single training example. This is in contrast to most machine learning methods which require a large number of training examples in order to learn and generalize well. One-Shot Learning is often used in situations where acquiring more training data is difficult or expensive.

Some of the emerging trends in One-Shot Learning include the use of deep learning models, the use of transfer learning, and the use of data augmentation.

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