Book Description
Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide,developers and data scientists will discover how graph analytics deliver value, whether they’re used for building dynamic network models or forecasting realworld behavior.
Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficulttofind patterns—from finding vulnerabilities and bottlenecksto detecting communities and improving machine learning predictions. You’ll walk through handson examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics.
 Learn how graph analytics reveal more predictive elements in today’s data
 Understand how popular graph algorithms work and how they’re applied
 Use sample code and tips from more than 20 graph algorithm examples
 Learn which algorithms to use for different types of questions
 Explore examples with working code and sample datasets for Spark and Neo4j
 Create an ML workflow for link prediction by combining Neo4j and Spark
Table of Contents
 Preface
 Foreword
 1. Introduction
 2. Graph Theory and Concepts
 3. Graph Platforms and Processing
 4. Pathfinding and Graph Search Algorithms
 5. Centrality Algorithms
 6. Community Detection Algorithms
 7. Graph Algorithms in Practice

8. Using Graph Algorithms to Enhance Machine Learning
 Machine Learning and the Importance of Context
 Connected Feature Extraction and Selection

Graphs and Machine Learning in Practice: Link Prediction
 Tools and Data
 Importing the Data into Neo4j
 The Coauthorship Graph
 Creating Balanced Training and Testing Datasets
 How We Predict Missing Links
 Creating a Machine Learning Pipeline
 Predicting Links: Basic Graph Features
 Predicting Links: Triangles and the Clustering Coefficient
 Predicting Links: Community Detection
 Summary
 Wrapping Things Up
 A. Additional Information and Resources
 Index
Product Information
 Title: Graph Algorithms
 Author(s):
 Release date: May 2019
 Publisher(s): O'Reilly Media, Inc.
 ISBN: 9781492047674