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Data and Visual Analytics (CSE6242) as part of Georgia Tech Master of Science in Analytics degree.

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Property-Investment-ROI-Analysis

Data and Visual Analytics (CSE6242) as part of Georgia Tech Master of Science in Analytics degree.

Project Purpose

How can you select properties that maximize return on investment (ROI) when investing in real estate? We answered this by building an algorithm which determines ROI based on user-selected features. We combined real estate listings, historical home appreciation/depreciation values, data enrichment algorithms, and external resources to calculate ROI for people interested in real estate investing. All of this is packaged in a clean user interface, enabling users to explore potential investments in an online interactive tool.

Demo Video:

Investment Property Analysis Tool on YouTube (3 mins)

Visualization

There are two different styles of displaying our data after the user selects filters based on his/her investment requirements: For requests with filters that return greater than 100 results, the UI will display circles centered on each Zipcode of the data, size scaled based on the number of properties within that zip code.

Investment Tool Large

For requests with filters that return less than 100 results, the UI display plots of each property on their corresponding GPS coordinates.

Investment Tool Small

Final Poster

Investment Tool Final Poster

Collaboration

This project was completed as a group of very talented data scientists and computer scientists:

  • Jasmine Fu
  • Sun Choi
  • David Mosto
  • Jeff Knapp

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Data and Visual Analytics (CSE6242) as part of Georgia Tech Master of Science in Analytics degree.

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