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NostraDomicile

The goal of the NostraDomicile Project is to create a web application whose two main functions are to predict whether a house will sell in a specific area based on the home’s attributes, and given a zip code, what are the most important factors leading to a sale in that area.

NostraDomicile will accomplish this goal by retrieving and storing housing market information using a Zillow API and MySQL database, using machine learning to evaluate housing data and determine factors influencing home sales in a particular area, and creating a user-friendly interface for users to view data about factors influencing home sales and create data visualizations about houses on the market based on user preferences

Requirements:

  • Zillow account to obtain Zillow API ID
  • PyZillow Module to utilize API
  • Server on local host or hosting service(We use AWS)
  • MySQL Relational Database(Also hosted on AWS)
  • Web Application Backend(Django Framework, Python for Machine Learning)
  • Web Application Frontend(AngularJS and Bootstrap)

System Model with Data Flow:

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Contributors:

  • Richard Andrews(Backend)
  • Ochaun Marshall(Machine Learning)
  • Christian Simaan(Database)
  • Jeremy Hutton(Front End)

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