Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task. Transfer Learning differs from traditional Machine Learning in that it is the use of pre-trained models that have been used for another task to jump start the development process on a new task or problem.
This repository contains various use cases where we apply transfer learning techniques to solve a particular business problem.
Refer Keras Applications to know about all the available Transfer Learning techniques. You can also checkout my kaggle page to dive deeper.