What is Transfer learning in Deep Learning?

Transfer Learning:

• It is a machine learning method where a model is developed for the task and is again used as the starting point for a model on a second task.

• It is a popular approach in deep learning where pre-trained models are used as the starting point for computer vision and natural language processing tasks are given the vast computing and time resources required to develop neural network models on these problems.

• Transfer learning is a machine learning technique where a model trained on one task is re-purposed on a second related task.

• Transfer learning is an optimization that allows rapid progress or improved performance when modeling the second task.

• Transfer learning only works in deep learning if the model features learned from the first task are general.