Graphs from Real-World Data you own this product

prerequisites
intermediate Python • intermediate pandas (read and query csv files)
skills learned
intermediate Neo4j (graph query using the Cypher language, loading and viewing graphs via Neo4j Desktop)
John Maiden
1 week · 6-8 hours per week · INTERMEDIATE
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New York City real estate is a trillion-dollar market, and you’ve got your eye on a collection of prime NYC properties whose value will likely double in a couple of years. They’re not currently for sale, but with your excellent sales skills, you’re confident you can get the owners to sell at a fair price, if you can only determine who the owners are. To obtain the owners’ contact data, you’ll construct a knowledge graph from publicly available data that contains tax records, property deeds, and permits. You’ll scan the data for the target owners, analyze the datasets for possible relationships, develop a knowledge schema that can extract insights into your use case, and load the data into Neo4j to query and visualize the connections. When you’re done, you’ll have practical experience applying widely used graph tools to real-world data, and you’ll understand how different choices for your graph schema can lead to different insights.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

John Maiden

John Maiden is a software engineer with a focus on building recommendation systems in the social media space. He’s given presentations about his work at Data Council and ML Conf, and he’s talked about building knowledge graphs on the Data Engineering Podcast. John has built knowledge graphs for real estate at a startup and has worked at JP Morgan Chase, where he led a team that produced personalized insights that were delivered to millions of Chase customers. He has a BA from Hamilton College and a PhD in Physics from University of Wisconsin–Madison.

prerequisites

This liveProject is for data scientists who have a background in data mining and graph theory and are interested in applying these techniques to constructing a knowledge graph. To begin these liveProjects you’ll need to be familiar with the following:

TOOLS
  • Intermediate Python 3.x skills
  • Ability to create lambda functions and list comprehensions
  • Intermediate Jupyter Notebook skills
  • Ability to execute and debug cells
  • Intermediate pandas (including visualizing pandas output)
  • Ability to read, write, and query data from CSV files
TECHNIQUES
  • Intermediate data mining
  • Analyze datasets
  • Use SQL-like commands to query and aggregate data
  • Basic graph theory

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