Abstract: Curious as to what graph data science (GDS) is all about? Come get a refresher on graph, graph data science, and how you can get value out of the connections in your data! This workshop will provide you with a crash course in how to leverage graphs by expanding your data science workflows. The hands-on section focuses on providing concrete examples of how to interact with the Neo4j database from a python notebook, create graph-y features, work with graph specific ML algorithms and how to leverage these results. Newbies to graph data science as well as experienced graph practitioners are welcome to join and dive into the GDS (Graph Data Science) Library.
○ Graph Technology and Graph Data Science
○ Value Proposition - Why should you care?
● Real-world applications of Graph Data Science
○ Classes of Algorithms and applicable Use Cases
● Graph-powered Machine Learning (Hands-on tutorials)
○ Connecting to the Sandbox
○ Centrality and Influence
○ Community Detection
○ Best Practices Q&A
● Recommended pre-work:
○ Create a Neo4j Sandbox Account
● Optional pre-work:
○ 5 Graph Data Science Basics Everyone Should Know
○ Youtube: Graph Data Visualization for Data Scientists and Data Analysts
Anyone with a desire to learn more about graph data science!
Bio: Alison Cossette is a dynamic Data Science Strategist, Educator, Responsible AI Advocate and Podcast Host. Her unique blend of technical expertise and communication skills has enabled her to communicate complex technical concepts in a way that decision-makers can understand and align data science strategies with broader business goals.
Alison is also a passionate advocate for responsible AI. She has developed and taught courses on responsible AI, machine learning, and data ethics, in addition to conducting research in Human-Computer Interaction at Stanford University. She firmly believes in the importance of ethical and transparent AI practices and strives to promote awareness and understanding of these issues. Alison studied at Northwestern University’s Master of Science in Data Science program with a specialization in Artificial Intelligence.