Transfer learning is the ability to apply knowledge learned in one context to a different but related context. This concept is relevant both in the field of machine learning and in the study of human learning and cognition, which is sometimes referred to as “brain learnography”. Both machine learnography and brain learnography benefit from transfer learning, as it allows knowledge transfer to be applied in new and different ways, leading to more efficient learning and better performance. In machine learnography, transfer learning refers to the ability to use knowledge gained from one machine learning task to improve performance on a different task. For example, a model that has been trained to recognize objects in photographs could potentially be used to identify objects in video footage, even if the training data for the two tasks was not identical. #learnography #education #knowledge #brain #biology #research #neuroscience #success #teaching #learning #parents #students #teachers #future #life #educators #school #class #machine #contents #contex #dimension