Optimize City Infrastructure

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prerequisites
basic LynxKite • tables and their representation as CSV file • basic data science and machine learning
skills learned
represent a network infrastructure problem as a graph optimization problem • the prize-collecting Steiner-tree problem • convert your business input data into the parameters of an abstract mathematical problem
Andras Nemeth
1 week · 6-8 hours per week · BEGINNER
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In this liveProject, you’ll use graph data optimization to determine improvements that could be made to the water infrastructure of Bruges. You’ll incorporate business data into your visualized Bruges street graph, and translate your graph into a prize collecting Steiner tree problem. You’ll then use the PCST solver in LynxKite to get an exact answer to your business problem.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Andras Nemeth
András Németh is the CTO of Lynx Analytics, with significant experience (as the top technology executive on client projects) in using graphs in real-world consultancy projects. He also led the development of LynxKite, a Graph Data Science Platform in the past six years. He has an MsC in Software Engineering and an MsC in Mathematics. Before Lynx Analytics, he worked for Google where he was the tech lead on a project aiming to annotate web pages with entities from Google's Knowledge Graph.

prerequisites

This liveProject is for data scientists interested in the basic techniques of graph data science. This project is suitable for all levels of expertise, from beginners to experienced practitioners. To begin this liveProject, you will need to be familiar with:

  • Basic LynxKite
  • Tables and their representation as CSV file
  • Basic data science and machine learning

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