MANAGEMENT

Detailed explanation-1: -Transfer learning allows developers to circumvent the need for lots of new data. A model that has already been trained on a task for which labeled training data is plentiful will be able to handle a new but similar task with far less data. There are other benefits of transfer learning through deep learning as well.

Detailed explanation-2: -Transfer of learning occurs when the student is motivated by the topic, motivated to learn, has previous knowledge on the subject, and knows how to connect new information to existing information. The learner must then be able to retrieve this information and apply it to new learning.

Detailed explanation-3: -Positive transfer refers to the facilitation, in learning or performance, of a new task based on what has been learned during a previous one. Negative transfer refers to any decline in learning or performance of a second task due to learning a previous one.

Detailed explanation-4: -Transfer learning is all about how a student applies learning in a discipline across multiple situations or contexts. To transfer, students need to see across situations rather than explore one situation or learn more in a particular discipline. They need to reach out rather than dig deep.