Using Python to Snake Closer to Simplified Deep Learning

On today's episode of "The Interview" with The Next Platform, we discuss the role of higher level interfaces to common machine learning and deep learning frameworks, including Caffe. Despite the existence of multiple deep learning frameworks, there is a lack of comprehensible and easy-to-use high-level tools for the design, training, and testing of deep neural networks (DNNs) according to this episode's guest, Soren Klemm, one of the creators of Python based Barista, which is an open-source graphical high-level interface for the Caffe framework. While Caffe is one of the most popular frameworks for training DNNs, editing prototxt files in order to specify the net architecture and hyper parameters can become a cumbersome and error-prone task. Instead, Barista offers a fully graphical user interface with a graph-based net topology editor. Barista is designed on top of the Caffe infrastructure.