EasyGML: A Fully-functional and Easy-to-use Platform for Industrial Graph Machine Learning

Abstract

Despite the great success of Graph Machine Learning (GML) in a variety of applications, the industry is still seeking a platform which makes performing industrial-purpose GML convenient. In this demo, we present EasyGML, a fully-functional and easy-to-use platform for general AI practitioners to apply out-of-the-box GML models in industrial scenarios. Leveraging the distributed data warehouse as its data infrastructure, EasyGML adopts AGL, an integrated system for industrial-purpose graph learning, as its core GML engine, and develops a model zoo containing various GML models, supporting both node property prediction and link property prediction. It packs different steps of GML workflow into different components, and provides a user-friendly web-based GUI for users to build their GML workflows simply by connecting several components together, without any coding.