Introduction

In this course, you will learn how to build a product recommendation system using Neo4j.

You will learn:

• Graph fundamentals: NodesiFull definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties., relationshipsiFull definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node., propertiesiFull definition for property (opens in a new tab)A named value stored on a node or a relationship., and CypheriFull definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. patternsiFull definition for pattern (opens in a new tab)A graph structure written in Cypher, such as a node joined to another node by a relationship.
• Performance model: How anchor nodes and traversaliFull definition for traversal (opens in a new tab)Following relationships from one node to the next to reach other parts of a graph. make queries fast
• Modeling decisions: When to use nodes vs. relationships vs. properties
• Import workflow: Using Neo4j's Import tool to load CSViFull definition for LOAD CSV (opens in a new tab)The Cypher clause that reads a CSV file row by row, so those rows can be written into the graph. data
• Query patterns: Multi-hop traversals and collaborative filtering