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segmentation clustering folium-maps foursquare-api unsupervised-learning web-scrapping data-visualization data-handling

segmenting-and-clustering-neighbourhoods-in-toronto-project's Introduction

Segmenting-and-Clustering-Neighbourhoods-in-Toronto-Project

!Important : Maps in the notebook can be seen from photos in repo or by running the notebook on Jupyter Notebook

This project's data is scraped from wikipedia (https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M)

Foursquare API is used to explore neighborhoods in Toronto

Neighbourhoods are grouped into clusters by using explore function to get the most common venue categories in each neighborhood

K-Means is used for clustering

Folium library is used to visualize the neighborhoods in Toronto and their emerging clusters.

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