Principles of Data Science
Transfer learning is a machine learning technique where a model developed for a specific task is reused as the starting point for a different but related task. This approach leverages knowledge gained from one domain to improve learning and performance in another, reducing the time and data needed for training new models. It is particularly effective in scenarios where the target dataset is small or lacks sufficient labeled data, allowing for faster convergence and better performance.
congrats on reading the definition of transfer learning. now let's actually learn it.