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Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Graph Algorithms : Practical Examples in Apache Spark and Neo4j
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Graph Algorithms : Practical Examples in Apache Spark and Neo4j
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 104.48
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Graph Algorithms : Practical Examples in Apache Spark and Neo4j
Language: English
Published by O'reilly Media Jun 2019, 2019
ISBN 10: 1492047686 ISBN 13: 9781492047681
Taschenbuch. Condition: Neu. Neuware - 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 patternsfrom 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.
