MLOps tools are increasingly used to ensure a structured ML pipeline from which to obtain good results and improve them over time.
Feast is a Feature Store, an important component for these pipelines and we will see how to use it starting from a graph DB like Neo4j and how to load useful data to train Graph Neural Network.
The data is moved from Neo4j to Postgres to create the Offline Store for Feast, so we will talk about what the loading process can be and the associated problems up to preparing the input for GNN