Transfer learning using neon - Nervana

In the last few years plenty of deep neural net (DNN) models have been made available for a variety of applications such as classification, image recognition and speech translation. Typically, each of these models are designed for a very specific purpose, but can be extended to novel use cases. For example, one can train a model to recognize numbers and characters in an image and then reuse that model to read signposts in a broader model or a dataset used in autonomous driving. Consider the task of visual classification. Convolutional neural networks (CNN) are organized into several layers with each layer learning features at a different scale.