Link Prediction: Fill the Blanks and Predict the Future!Thursday, October 7.8:00 a.m. PT | 11:00 a.m. ET | 16:00 BST | 17:00 CEST
Link prediction is all about filling in the blanks – or predicting what’s going to happen next. In a graph, links are the connections between concepts: knowing a friend, buying an item, defrauding a victim, or even treating a disease.
Our newest GDS (Graph Data Science) library release 1.7 adds the ability to define and run pipelines for supervised machine learning (ML). This means you can define the features you want to use, and we’ll handle splitting your data, calculating your features, and picking the best model for your problem.
Want to learn more about how to use Neo4j and GDS for link prediction? Join us Thursday, October 7, for a deep dive to learn:
- How link prediction works
- How to adjust for sparse or biased data
- How to define and run pipelines for supervised machine learning
- And, see this demonstrated on a real world data set
Aimed at data scientists and data professionals – whether new to using graphs in data science, or an expert looking to wring a few extra percentage points of accuracy out of your data – you’ll learn how using the Neo4j Graph Data Science (GDS) library makes your job easier.
I hope you can join us!
Dr. Alicia Frame
Director of Product Management, Graph Data Science