This lunch session introduces you to our DGL adapter. We walk through the base examples of how to use the adapter to export ArangoDB graphs to DGL. The Deep Graph Library (DGL) is an easy-to-use, high-performance, and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component of an end-to-end application, the rest of the logic can be implemented in any major frameworks, such as PyTorch, Apache MXNet, or TensorFlow.
About the Presenter:
Anthony Mahanna is a student pursuing an Honours Bachelor’s degree in Computer Science at the University of Ottawa (ON, Canada). He has internship experience in DevOps and microservice development and has worked on side projects that have impacted students at his school. Anthony has recently discovered ArangoDB and created Picsum Vision to explore its functionalities