Zillow awards $1 million to team that reduced home valuation algorithm error to below 4%

  • “The Seattle company today announced that team ChaNJestimate — whose members include Chahhou Mohamed, Jordan Meyer, and Nima Shahbazi, hailing from Morocco, the U.S., and Canada, respectively — will take home the $1 million prize for a model that bested the Zillow “Zestimate” benchmark by approximately 13 percent. (The Zestimate’s nationwide error rate is 4.5 percent; the team’s work pushes it to below 4 percent.)
  • To achieve this new level of accuracy, team ChaNJestimate leveraged deep neural networks — layers of mathematical models modeled after neurons in the brain — and other machine learning techniques to “directly” estimate home values
  • Currently, the Zestimate is within $10,000 of a given home’s sale price, and Zillow expects the improvements could bring it $1,300 closer to the actual price.”


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