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How to identify clusters and name them
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Unsupervised algorithms for clustering
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Selecting the number of clusters
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Naming clusters
Cluster Models
Learn how to identify clusters and name them
In this course we will study in details the machine learning aspect of our Geographic clustering sample project.
The aim of this project is to segment neighborhoods of Manhattan and Paris based on the type of locations and events that are present. Based on data from Open Street Map and Foursquare, we aggregate points of interest by type and count how many venues are present in each neighborhood.
This data serves as the basis for a clustering algorithm that will classify neighborhoods by type.
If you want to see how we achieve this, especially regarding data ingestion and preparation, you can find details in the project’s description.