Transfer learning

Transfer learning is a technique in the field of machine learning in which a model trained on one task is applied to another similar task. Instead of training a model from scratch, previously learnt features and knowledge from a source task are transferred to the target task. This makes it possible to create effective models with less data and computing resources. Transfer learning is widely used in areas such as image recognition, natural language processing and language translation.