Abstract: 

This workshop focuses on why Graphs are currently one of the biggest trends in Machine Learning. While many traditional techniques focus on isolated entities, neglecting the context, GraphML explicitly considers the context and relationships between different data items, leading to more precise and faster insights.

In this workshop, we will provide a hands-on introduction to Graph Machine Learning, including topics such as Graph Embeddings, Graph Neural Networks, and different applications of Graph Machine Learning. In particular, we will cover the following topics:
- The value of Graph in an interconnected world 
- Graph Machine Learning techniques
- End-to-end Graph Machine Learning

Background Knowledge:

The workshop is hands-on, leveraging Jupyter notebooks, so there is no need to pre-install software and there are no prerequisites.

Bio: 

Jörg Schad is the ArangoDB CTO. Previously, he worked on Machine Learning Infrastructure in health care, distributed systems at Mesosphere, implemented distributed and in-memory databases, and conducted research in the Hadoop and Cloud area. He frequently speaks at meetups, international conferences, and lecture halls. Jörg is fluent in three languages and passionate about science & technology, education, and the environment.