Transfer Learning

Transfer Learning is a Machine Learning technique where a model developed for a specific task is reused as the starting point for a model on a second task. This approach leverages knowledge gained while solving one problem and applies it to a different but related problem, ultimately improving performance and reducing training time.

For instance, a model trained on a large dataset of images (like ImageNet) can be fine-tuned to recognize specific types of medical images, such as X-rays. Another case is using a language model pre-trained on a vast corpus of text and adapting it for sentiment analysis in product reviews.