Clarifying Enterprise Deep Learning Development Priorities

Premise Deep learning developers are beginning to adopt open modeling frameworks that mitigate the risks of being locked into any of the myriad of tools in this vigorously competitive field. Analysis Deep learning (DL) is infusing diverse applications in the cloud and at the network’s edge, especially in embedded, mobile, and Internet of Things & […]

Assessing Deep-Learning Development Frameworks

Premise Deep learning developers are gravitating toward the leading modeling frameworks, most notably, TensorFlow, MXNet, and CNTK. In addition to having well-developed ecosystems, these frameworks enable developers to compose, train, and deploy DL models in in their preferred languages, accessing functionality through simple APIs, and tapping into rich algorithm libraries and pre-defined modular components. Analysis […]