What is transfer learning?

Transfer learning is the use of data collected by a neural network to simplify the process of collecting and training another network.
Unsupervised transfer learning is a type of learning based on the acquisition of unlabeled data.
Transductive transfer learning takes a structure with similar functions and objectives, but the programmer will have to customize it with their own data.
The success of transfer learning is the development of pre-trained neural networks in the open-source branch that allow more programmers to enter this constantly growing world.
a) Only statement 1 is correct.
b) Statements 1, 2, and 3 are correct.
c) Statements 1, 2, 3, and 4 are correct.
d) Only statement 4 is correct.