Abstract: 

Thinking about adding relationships to improve your machine learning predictions? Or maybe you’re creating a knowledge graph for investigating dependencies or finding counterfactuals.

Join us for a demo of the Neo4j Graph Data Science platform that is designed specifically for graphs with 60+ supported, scalable graph algorithms from pathfinding and similarity to influencer and community detection.

We will demo:

- Several algorithms, like pathfinding, centrality, similarity
- Cutting edge tech with graph embeddings and model training
- Supervised machine learning for predicting unobserved or future relationships
- No-code visualization and prototyping with Bloom

You’ll leave this demo with essential resources for predictive modeling and analytics with graph technology.

Bio: 

Joe has over 20 years of varied experience in the IT industry across a number of industries, domains, and specialties. For most of the last decade he has focused on technical pre-sales and solution architecture for data and analytics. Joe is especially passionate about graph databases and graph data science, and is thrilled to work for the leader in this space - Neo4j.

When not geeking out over data and technology he enjoys camping and hiking with his dog, tending to his garden, reading, and playing all manner of video and tabletop games. He also bakes a mean cheesecake.