SwoopGT/Clustering-Toronto-Neighbourhoods-using-Folium-and-Clustering

Clustering of toronto neighbourhoods into various clusters is done based on the venues in each neighbourhood. The project acts as a ground work for the future project - Site Selection using K-Means Clustering.

Clustering-Toronto-Neighbourhoods

The city of Toronto is made up of various neighbourhoods. These neighbourhoods host numerous venues distributed in and around them.

Using foursquare API and Folium library, the location and venue data of each neighbourhood is obtained.

Using Machine Learning Clustering - K-Means Clustering the venues are clustered together.

The top 5 venue clusters are displayed and the similarity within clusters is highlighted.

Observations are noted and necessary conclusions are reached.

This project acts as a ground work for the project - Site Selection using K-Means Clustering which deals with a real life problem.