Graph Algorithms: Practical Examples in Apache Spark and Neo4j (Mark Needham, et al)

 
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Graph Algorithms: Practical Examples in Apache Spark and Neo4j (Mark Needham, et al)

Learn how to use the relationships in your data to your advantage by using graph algorithms to create smarter solutions and improve your machine-learning models.

Developers and data scientists will learn how to graph analytics add value, whether they are used to create dynamic network models or forecast real-world behavior, with the help of this useful book.

For engineers and data scientists who have prior familiarity with Apache Spark or Neo4j, this book serves as a practical introduction to getting started with graph algorithms. Regardless of the graph technology you choose to use, this book will be useful for understanding more fundamental graph ideas even if our algorithm examples use the Spark and Neo4j platforms.

It illustrates how graph algorithms characterize complicated systems and make difficult-to-find patterns visible, from identifying bottlenecks and weaknesses to identifying communities and enhancing machine learning predictions. You will be guided through practical examples that demonstrate how to employ graph algorithms in Neo4j and Apache Spark, two of the most popular options for graph analytics.

  • Learn how to 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

Ebook Details

About the Authors
  • At Neo4j, Mark Needham is a Developer Relations Engineer and a supporter of graphs. Mark assists users in adopting Neo4j and graphs to create complex solutions to difficult data challenges.
  • Amy Hodler is the AI and Graph Analytics Program Manager at Neo4j and an enthusiast of network science. She advocates the use of graph analytics to identify patterns in actual networks and forecast changing behavior.
Published
Published Date / Year
1 edition (May 26, 2019); eBook (Compliments of Neo4j)
Hardcover
256 pages
eBook Format
PDF (257 pages), ePub, and Mobi (Kindle)
Language
English
ISBN-10
1492047686
ISBN-13
978-1492047681

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