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.