Free O’Reilly Book: Graph Algorithms in Apache Spark and Neo4j

Grab your free copy of the brand new O’Reilly book, “Graph Algorithms: Practical Examples in Apache Spark & Neo4j” – a practical guide to graph analytics.

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Graph Algorithms in Neo4j: Triangle Count & Clustering Coefficient

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Louvain Modularity

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Weakly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Strongly Connected Components

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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Graph Algorithms in Neo4j: Closeness Centrality

Graph algorithms provide the means to understand, model and predict complicated dynamics such as the flow of resources or information, the pathways through which contagions or network failures spread, and the influences on and resiliency of groups. This blog series… Read more →

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