What’s Transfer Learning? 

Transfer learning is a key training method in machine learning where a model trained on one task is used to help perform a related task. This involves pre-training a model on a large dataset and then fine-tuning it on a smaller, task-specific dataset. By leveraging what the model has already learned, transfer learning makes the process of learning a new task faster and more effective. It's akin to using skills learned in one job to quickly excel at a new, similar job. This approach accelerates and improves performance on the new task, making it easier to achieve good results.