Pinaki Laskar on LinkedIn: #DataScientist #ArtificialIntelligence #DataAnalytics

Transfer learning (TL) in machine learning (ML) that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem. For example, knowledge gained while learning to recognize cars could apply when trying to recognize trucks. Transfer learning is the reuse of a pre-trained model on a new problem. It's currently very popular in deep learning because it can train deep neural networks with comparatively little data. Importance of transfer of learning, The main purpose of any learning or education is that a person who acquires some knowledge or skill in a formal and controlled situation like a classroom, or a training situation, will be able to transfer such knowledge and skill to real life situations and adapt himself more effectively.