11 What’s next: Graph analytics, machine learning, and resources

 

This chapter covers

  • Graph analytics algorithms for pathfinding, centrality, and community detection
  • Graphs in machine learning (ML)
  • Helpful resources for graph theory, graph databases, and graph algorithms

Great! You’ve made it to the final chapter. It’s been a journey as we’ve switched from thinking about problems from a relational, entity-first mindset to a graph, entity-plus-relationships mindset. Even though this is the end of the book, the next phase of your journey with graphs is just beginning. So what’s next? Where do you go from here? This chapter answers these questions by providing an overview of common paths many people pursue in extending their knowledge of graphs.

Graph analytics and machine learning (ML) are two of the most common areas where exploration of graphs might take you next. This chapter introduces these two concepts and provides you with just enough information to decide if you want to explore these areas further.

11.1 Graph analytics

 
 
 

11.1.1 Pathfinding

 
 

11.1.2 Centrality

 
 
 

11.1.3 Community detection

 
 

11.1.4 Graphs and machine learning

 
 
 
 

11.1.5 Additional resources

 
 
 

11.2 Final thoughts

 
 
 
 

Summary

 
 
 
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