Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. Youll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver valuefrom finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions.This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4jtwo of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection.Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark
Amy E. Hodler & Mark Needham
Graph Algorithms [EPUB ebook]
Practical Examples in Apache Spark and Neo4j
Graph Algorithms [EPUB ebook]
Practical Examples in Apache Spark and Neo4j
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भाषा अंग्रेज़ी ● स्वरूप EPUB ● पेज 268 ● ISBN 9781492047636 ● प्रकाशक O’Reilly Media ● प्रकाशित 2019 ● डाउनलोड करने योग्य 3 बार ● मुद्रा EUR ● आईडी 7016552 ● कॉपी सुरक्षा Adobe DRM
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