What is transfer learning in AI?

What is transfer learning in AI?

Transfer learning is a technique where a model developed for a specific task is reused as the starting point for a model on a second task.

How does it differ from traditional machine learning?

In traditional machine learning, models are trained from scratch on a specific dataset, while transfer learning leverages pre-trained models to improve efficiency and performance.

Can you give me an example of transfer learning in action?

Sure! A common example is using a model trained on ImageNet to classify images in a different domain, like medical images.

What are the benefits of using transfer learning?

Benefits include reduced training time, improved performance with less data, and the ability to leverage existing knowledge.