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Books > Computing & IT > General theory of computing > Data structures
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Graph Algorithms - Practical Examples in Apache Spark and Neo4j (Paperback)
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Graph Algorithms - Practical Examples in Apache Spark and Neo4j (Paperback)
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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
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