Look inside
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.
book resources
When you start your liveProject, you get full access to the following books for 90 days.
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 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
features
- Self-paced
- You choose the schedule and decide how much time to invest as you build your project.
- Project roadmap
- Each project is divided into several achievable steps.
- Get Help
- While within the liveProject platform, get help from other participants and our expert mentors.
- Compare with others
- For each step, compare your deliverable to the solutions by the author and other participants.
- book resources
- Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.