Relationships Matter - Using Connected Data for Better Machine Learning
Explore the power of connected data in machine learning through this 44-minute webinar from Open Data Science. Learn how to leverage graph-native ML techniques to enhance predictive capabilities by incorporating relationship information. Discover different approaches to graph feature engineering, including queries, algorithms, and embeddings. Dive into ML techniques that utilize classical network science, deep learning, and graph convolutional neural networks. Gain hands-on experience in generating graph representations, creating ML models for link prediction and node classification, and applying these models to enrich existing graphs or incoming data. Understand the importance of no-code visualization and prototyping in graph-based ML. Follow along with a practical demonstration that covers exploring graphs, projecting subgraphs, calculating features, and making predictions using Neo4J and graph data science tools.