This Week in Neo4j – DeepGL on Peer to Peer Network, Relational to Graph with APOC, Global Power Emissions Database

This week in Neo4j has seen the release of several new features and applications, including DeepGL's use for extracting features from peer-to-peer networks, APOC's import functionality for relational data, and Agent Smith 2.0, a "top" application that now watches transactions for stability. Graphs have also been explored in relation to AI, with Morgan Vawter writing an article on the topic and Bajal showing how to visualize a Kubernetes cluster using Neo4j. Additionally, there's been news from GraphConnect NYC 2018, including an experience report by Arina Igumenshcheva and a post by Igor Bobriakov on integrating Spark, GraphX, and Neo4j. The community has also featured Devansh Trivedi, who is using Neo4j for his "100 Days of Machine Learning" challenge, creating word-pair frequency graphs and content-based recommendation engines.

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