Transfer learning is a machine learning technique that involves using a pre-trained model as a starting point for a new model. This approach can significantly reduce the time and resources required to train a model and improve the performance of the model on a specific task. The use of transfer learning has become popular in several machine learning applications, including image recognition, natural language processing, and speech recognition.
