Learn how to utilize the ArangoDB-DGL adapter in this technical lunch session video that demonstrates exporting ArangoDB graphs to the Deep Graph Library (DGL). Master the fundamentals of DGL, a high-performance Python package for deep learning on graphs that works with major frameworks like PyTorch, Apache MXNet, and TensorFlow. Follow along with step-by-step examples covering adapter instantiation, bidirectional conversion between ArangoDB and DGL, and handling of unique cases. Access hands-on practice materials through the provided GitHub repository and Google Colab notebook while exploring DGL's comprehensive documentation for implementing deep graph models in end-to-end applications.
Overview
Syllabus
Intro
DGL Basics
Instantiating the adapter
ArangoDB to DGL
DGL to ArangoDB
Unique Cases 1
Unique Cases 2
Closing Remarks
Taught by
ArangoDB