Graph Algorithms for Data Science: With Neo4j Examples

Master the use of graph algorithms data science techniques with practical Neo4j examples. This comprehensive guide equips you with the skills to solve complex, connected data problems using graph-based approaches. Learn how to uncover hidden patterns, perform link predictions, and enhance data insights in domains like social networks, recommendation systems, fraud detection, and knowledge graphs.

What You’ll Learn

• Introduction to graph theory and data structures
• Core graph algorithms: PageRank, centrality, community detection
• Hands-on implementation using Neo4j Graph Data Science (GDS) library
• Working with real-world graph datasets
• Building intelligent applications using graph analytics
• Applications in cybersecurity, social networks, and recommendation engines
• Optimizing graph queries and interpreting results effectively

Requirements

• Basic understanding of Python or Cypher query language
• Fundamental knowledge of data structures and algorithms
• Familiarity with data science concepts

Book Description

This graph algorithms data science book bridges the gap between theory and practice. It explores how graph algorithms work under the hood, and how you can apply them to solve real-world problems using Neo4j—a leading graph database technology. You’ll start with foundational concepts of graph theory and then move into building, querying, and analyzing graph data using Neo4j’s Graph Data Science library.

Through guided examples and case studies, you will learn to use graph algorithms to detect communities, calculate influence scores, analyze relationships, and even recommend content based on structural proximity. By the end, you’ll be equipped to integrate graph intelligence into your data workflows and applications.

About the Author

Authored by experienced data scientists and Neo4j practitioners, this book combines academic rigor with applied insights. The content is ideal for data analysts, machine learning engineers, and developers exploring graph-powered solutions.

Explore These Valuable Resources

• Neo4j Graph Data Science Library
• Introduction to Graph Algorithms
• GeeksforGeeks: Graph Algorithms Overview

Explore Related Courses

• Data Science with Python
• Neo4j Graph Database Fundamentals
• Advanced Machine Learning Models
• Algorithms and Data Structures
• Building Intelligent Data Systems