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This project involves the use of K-Means Clustering to find the best accommodation for students in any city of your choice by classifying accommodation for incoming students on the basis of their preferences on amenities, budget and proximity to the location.

cntejas/Exploratory-Analysis-Of-Geolocational-Data

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Exploratory-Analysis-Of-Geolocational-Data

This project involves the use of K-Means Clustering to find the best accommodation for students in any city of your choice by classifying accommodation for incoming students on the basis of their preferences on amenities, budget and proximity to the location.

The project consists of the following stages:

ME_ME_PROJECT_GEODATA_ANALYSIS_MODULE_ME_PROJECT_GEODATA_ANALYSIS_MODULE_GEODATA_ANALYSIS_Project-Steps

Result after implementation

Screenshot 2022-07-15 160502

By Observation

  1. Cluster 0 (Green) has more restaurents but less gyms and cafes.
  2. Cluster 1 (Orange) has maximum restaurents,gyms and cafes.
  3. Cluster 2 (Red) has less cafes but more gyms and restaurents.

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This project involves the use of K-Means Clustering to find the best accommodation for students in any city of your choice by classifying accommodation for incoming students on the basis of their preferences on amenities, budget and proximity to the location.

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