Transfer Learning is a machine learning technique that involves taking a pre-trained model developed for a task and adapting it for use on a new and different task. This can be especially useful when the new task is similar to the original task, or when there is a shortage of data or resources to train a model from scratch. It also allows us to leverage the knowledge learned by a model on one task and apply it to a new task, potentially improving the performance of the new model.
