My submission for Coursera's IBM Applied Data Science Capstone course final project.
Click here to see more info about the course.
I used a geographical dataset of New York City subway stations along with the FourSquare API to:
- Categorize all stations based upon their surrounding venues.
- Use k-means clustering to explore possible correlations of interest.
This information could be useful for city planners to predict the amount of traffic during certain times at specific subway stations and their surrounding areas.