GitHub / Blaise-Tsh / Segmentation-and-Clustering-of-Neighborhoods-in-Toronto
Toronto is the provincial capital of Ontario and One of the most populous city in Canada and the fourth most populous city in North America. In 2016, foreign-born persons made up 47% of the population, compared to 49.9% in 2006. This project is an application of data science techniques to analyse Toronto City neighborhoods geospacial data in order to explore the similarity trends of venues and classify them into groups of most common characteristics. Foursquare API was used for neighborhoods exploration and K-Means clustering algorithm for classification. Folium library was used to visualize venues on the Toronto map.
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PURL: pkg:github/Blaise-Tsh/Segmentation-and-Clustering-of-Neighborhoods-in-Toronto
Stars: 1
Forks: 0
Open issues: 0
License: None
Language: Jupyter Notebook
Size: 103 KB
Dependencies parsed at: Pending
Created at: about 5 years ago
Updated at: almost 2 years ago
Pushed at: almost 5 years ago
Last synced at: almost 2 years ago
Topics: clustering-methods, neighborhood, segmentation, toronto