MXNet is open source library for DL with broad API language support for R, Python, Julia and other languages [Chen 2015]. It is developed by Pedro Domingos and a team of researchers at the University of Washington, it is also a part of the DMLC [DMLC]. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on-the-fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines. It is licensed under an Apache-2.0 license. MXNet is supported by major public cloud providers. It also supports an efficient deployment of a trained model to low-end devices for inference, such as mobile devices (using Amalgamation Amalgamation), IoT devices (using AWS Greengrass), Serverless (Using AWS Lambda) or containers.