What is Transfer Learning? - KDnuggets

Transfer Learning is a machine learning method where the application of knowledge obtained from a model used in one task, can be reused as a foundation point for another task. Machine learning algorithms use historical data as their input to make predictions and produce new output values. They are typically designed to conduct isolated tasks. A source task is a task from which knowledge is transferred to a target task. A target task is when improved learning occurs due to the transfer of knowledge from a source task.