Transfer Learning With Apache Spark and Big DL

Transfer learning with Spark and BigDL allows users to take pre-trained deep learning models and reuse them to solve new problems. This technique involves "freezing" the earlier layers of a pretrained model and retraining only the last few layers on new data. This speeds up the training process and helps achieve good results with less data. The document provides examples of using transfer learning with image classification models like Inception to retrain the final layers on new datasets of images.