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 bottlenecks to 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
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 bottlenecks to 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
Mark Needham is a graph advocate and Developer Relations Engineer
at Neo4j. Mark helps users embrace graphs and Neo4j, building
sophisticated solutions to challenging data problems. Mark has deep
expertise in graph data having previously helped to build Neo4j's
Causal Clustering system. Mark writes about his experiences of
being a graphista on a popular blog at markhneedham.com.
Amy Hodler is a network science devotee and AI and Graph Analytics
Program Manager at Neo4j. She promotes the use of graph analytics
to reveal structures within real-world networks and predict dynamic
behavior. Amy helps teams apply novel approaches to generate new
opportunities at companies such as EDS, Microsoft, Hewlett-Packard
(HP), Hitachi IoT, and Cray Inc. Amy has a love for science and art
with a fascination for complexity studies and graph theory.
|
Ask a Question About this Product More... |
|
