Data scientists at the company are developing convolutional neural networks, computer systems designed to mimic the human brain, trained to correlate specific collections of image pixels with valuation signals. For example, if granite countertops and stainless steel are identified in a photograph, that will automatically signal an increase in price.
“It’s essentially trying to code, in the pattern of a neural network, what we as humans can infer just by looking at the image,” said Stan Humphries, chief analytics officer, who heads the firm’s 100-person analytics division.
The deep-learning approach on image data could be integrated into the company’s valuation algorithm, called a “Zestimate,” during the first quarter of 2017, he said.