What is Transfer Learning Transfer learning or inductive transfer is a research problem in machine learning 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. This area of research … Transfer Learning – Some available Pre-trained models for TensorFlow, PyTorch, Keras and CNTK weiterlesen