Graph Algorithms: Practical Examples in Apache Spark and Neo4j
Authors: Mark Needham – Amy E. Hodler
ISBN-10: 1492047686
ISBN-13: 9781492047681
Edition 版次: 1
Publication Date 出版日期: 2019-05-26
Print Length 页数: 256 pages
Book Description
By finelybook
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 real-world behavior.
Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns—from finding vulnerabilities and bottlenecksto detecting communities and improving machine learning predictions. You’ll walk through hands-on 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
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
A.Additional Information and Resources
Index
