This Week in Neo4j – Building a low-code platform, Beer Recommendations, Building A GRANDstack Real Estate Search App

This week, the Neo4j community has been actively engaged with various projects and topics. Will Lyon started a series on building a GRANDstack Real Estate Search App, while Tomaz Bratanic explored the Node2vec embedding algorithm using Kaggle's Spoonacular Food Dataset. Meanwhile, Dan Flavin solved a triangle counting brain teaser, and Stefan Dreverman began a blog series on building a low-code platform with Neo4j. Mike Lam built a collaborative filtering-based recommendation engine based on beer data extracted from brewDB's Open API. The community also featured Stefan Dreverman as their member of the week, who is working as a freelance IT consultant in the Netherlands. Additionally, there were several other projects and topics covered, including a contact tracing testbed using Neo4j and Faker, an interview with Dr Alexander Jarasch from the German Center for Diabetes Research, and a tweet about AI accountability.

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