Skip to content

The repository is a part of the IBM Data Science Capstone project. The project includes the segmentation and clustering of Neighbourhoods in Toronto using K Means Machine Learning Clustering algorithm. To view the notebook, visit this website.

Notifications You must be signed in to change notification settings

namanmanchanda09/Segmenting-and-Clustering-Neighbourhoods-in-Toronto

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

16 Commits
 
 
 
 

Repository files navigation

Segmenting-and-Clustering-Neighbourhoods-in-Toronto

The repository is a part of the IBM Data Science Capstone project. The project includes the segmentation and clustering of Neighbourhoods in Toronto using K Means Machine Learning Clustering algorithm.

The first map contains the visualization of the various neighbourhoods in Canada whose borough has the word Toronto.

Screenshot 2019-07-27 at 9 41 35 PM

The second map contains the clusters of data using the KMeans ML algorithm.

Screenshot 2019-07-27 at 9 41 54 PM

To view the jupyter notebook on IBM Cloud, visit https://dataplatform.cloud.ibm.com/analytics/notebooks/v2/f345775d-d996-4035-9009-8ffb56057b22/view?access_token=98a0542961c0296219a57cbc7426269e33d7b1b96774b6eb55e8476bbdc8a0a3

About

The repository is a part of the IBM Data Science Capstone project. The project includes the segmentation and clustering of Neighbourhoods in Toronto using K Means Machine Learning Clustering algorithm. To view the notebook, visit this website.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published