Neo4j: Building Graphs with Neo4j's Graph Data Science Library

Neo4j 4.3.6    |    Beginner
  • 12 Videos | 1h 46m 17s
  • Includes Assessment
  • Earns a Badge
The Graph Data Science (GDS) library provides data scientists and developers with the necessary tools to perform powerful analysis of their graph data. In this course, you will look at various use cases of GDS and cover some of its essential operations. Begin with an overview of the GDS library and then dive into using the library by building in-memory graphs from the contents of your Neo4j database. Explore how to build graphs using native and Cypher projections. Next, apply a graph algorithm to your GDS graph and see how it can be used to obtain meaningful information about the nodes and relationships in your data. After completing this course, you will have a fundamental understanding of the GDS library for Neo4j and the necessary capabilities to build your own in-memory graphs and extract significant insights.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    list the main categories of graph algorithms and recall their use cases
    recognize the mechanism of creating and working with graphs in Neo4j's Graph Data Science library
    install the Graph Data Science library for a Neo4j DBMS
    create an in-memory graph using the native projection configuration for nodes and relationships
    use the page rank algorithm to compute a score for each node in a graph
  • load properties from a source database to an in-memory graph
    apply a Graph Data Science function to read a property from a graph
    build a graph using the Cypher projection by setting node and relationship queries
    create a Cypher projection graph with properties from the source database
    build a sub-graph containing a subset of elements from an already existing graph
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    2m 50s
    UP NEXT
  • Playable
    2. 
    An Overview of Graph Algorithms
    11m 9s
  • Locked
    3. 
    Using the Graph Data Science Library
    9m 48s
  • Locked
    4. 
    Setting Up the Graph Data Science Library
    8m 44s
  • Locked
    5. 
    Creating a Graph with Native Projection
    11m 19s
  • Locked
    6. 
    Applying a Page Rank Algorithm on a Graph
    11m 25s
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    7. 
    Projecting Properties in a Graph
    9m 15s
  • Locked
    8. 
    Accessing Properties from a Graph
    12m 2s
  • Locked
    9. 
    Creating Cypher Projection Graphs
    10m 23s
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    10. 
    Building Cypher Graphs with Properties
    5m 42s
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    11. 
    Building Subgraphs
    11m 27s
  • Locked
    12. 
    Course Summary
    2m 13s

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