In this liveProject, you’ll use LynxKite and graph data techniques to identify some of the most important geographic points in the city of Bruges. You’ll start by downloading and processing map data, and then use a simple Python program to convert it into a graph. You’ll use graph centrality metrics to quantify the importance of vertices in your graph, and determine some of Bruges’ important locations. You’ll then use the same structure to figure out the main areas of the city without using actual district data.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
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 Python
- Tables and their representation as CSV file
- Basic data science and machine learning
you will learn
In this liveProject, you’ll learn the basics of graph data structures and how to define relationships between data.
- Convert map data to a graph representation
- Visualize graphs
- Compute and use common centrality metrics
- Simple graph clustering techniques