Accelerate AI Development with Transfer Learning – Anjali Shah & Steve Ginger | ODSC East 2019
Training deep neural network models requires a tremendous amount of time, training data, and compute resources. A technique called transfer learning allows data scientists to increase their productivity dramatically by sharing neural network architectures and model weights. Reuse of a pre-trained model on a different but related task enables training of deep neural networks with comparatively less data. In this talk, you will learn the details of how transfer learning works and will see demonstrations in both financial and healthcare domains. This video will tell you about specific use cases and lessons learned that are applicable to many other industry sectors.