Building a Recommendation Engine Using Neo4j Hands-On — Part 2` is an in-depth guide on how to build a recommendation engine using Neo4j, a graph database. The article covers the process of loading data into Neo4j, creating relationships between nodes, and implementing a recommender system that answers three key questions: what does a user generally order most frequently, which items are frequently ordered along with an item amongst all users, and once a particular item has been added to the cart, which other items have been previously ordered by the user with it. The guide also discusses deployment options for Neo4j and serving recommendations through API endpoints.