Full Webinar: https://info.tigergraph.com/graph-gurus-28
In this webinar, we will use the recommendation system problem, which can be efficiently solved as a graph problem, to demonstrate the in-database training capability of TigerGraph, a native graph database. A hybrid (memory-based + model-based) recommendation system will be implemented in TigerGraph. Specifically, the latent factor model used for recommendation will be trained within the database.
In this Graph Gurus episode, we will:
-Review multiple widely-used recommendation methods
-Introduce the concept of in-database machine learning
-Present an in-database machine learning solution for a real time recommendation system