googlemapskey

Gain insights into solving the Traveling Salesperson Problem using Python. Learn about geospatial data manipulation, clustering, network graphs, and Docker to optimize route planning and data visualization.

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Solving complex computational problems is a resource-demanding task. The traveling salesperson problem (TSP) is one such problem, which is an NP-hard problem. In the era of data science, data-centric approaches have evolved to be a good choice to approximate the solutions. 

In this course, you’ll dive into the fascinating realm of geospatial data manipulation, distance calculation, clustering, network graphs, and Docker containerization, all tied together to optimize the challenging TSP. You’ll first grasp the intricacies of manipulating geospatial data and plotting it. Next, you’ll delve into clustering sales data, enhancing your ability to make data-driven decisions and visualize the data mining results in interactive dashboards.

By the end of this course, you’ll be skilled in tackling TSP effectively and creating geospatial data visualizations. You’ll also be well-equipped to scale route optimization, data analysis, and cloud deployment.

Solving the Traveling Salesperson Problem in Python

When developing a business application that requires hundreds of route requests, it’s advisable to use a commercial product like Google Maps. Similar to OSM in the prior lesson, we’ll query against a URL address to receive the distances. One of the main differences is the use of a paid Google Maps API key.





To get started, we first need to enable the API. Select your desired project in the GCP console to do this. If you need more information about this, please refer to the Appendix.






Elevate the performance of commercial applications with the power of Google Maps API and its advanced car distance measuring capabilities.

What the Traveling Salesperson Problem Is About

Preprocessing of Traveling Salesperson Data

Solving the Traveling Salesperson Problem

Traveling Salesperson Data Mining

Building the Traveling Salesperson Dashboard

Scalability

Conclusion

Appendix

Road Distance: Google Maps