cntejas/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.
This helps real estate agents, university housing departments, or student relocation services identify optimal student accommodations in any city. You provide student preferences (amenities, budget, desired proximity to a location) and receive classified housing options, making it easier to match students with suitable homes. This tool is for anyone helping students find housing.
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Use this if you need to efficiently group and recommend student accommodations based on their specific needs and location preferences.
Not ideal if you're looking for a tool that handles lease agreements, property management, or detailed financial analysis beyond basic budget matching.
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Last pushed
Sep 11, 2024
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