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.
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
you will learn
In this liveProject, you’ll learn the basics of graph data structures and how to define relationships between data.
- 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
- Solve graph optimization problems with LynxKite
- Handle incremental optimization
- 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.