Next week, Wayfair Data Science will be at the Computer Vision and Pattern Recognition conference in Salt Lake City. We’re bringing data scientists and engineers from several different teams, plus a VR rig to try out the shopping experience of the future (come find us at booth 224!). We pride……
Last year, Wayfair launched Visual Search, a new and novel way to find products on our website. Users can now upload photos of furniture they like and find visually similar matches in an instant. If you need a little refresher on this technology, the original blog post can be found……
Multiple recommendation systems at Wayfair use collaborative filtering based models to understand user behavior and identify like-minded customers. Despite its success, collaborative filtering has a few significant drawbacks, such as the cold start problem and a limited scope of recommendable products. By leveraging image based product embeddings, Wayfair has created……
These days, in the big data community, we often hear how biologists have adopted and are using distributed computing technologies that were first introduced to solve problems in software engineering. The fact that Wayfair has done the inverse and used a tool initially developed to help biologists cluster similar proteins……
Our story begins in Holland in 1997, where a researcher named Stijn van Dongen, who is pretty good at Go, has a 5-minute flash of insight into modeling flows with stochastic matrices. He writes a thesis about it and makes a toolkit called MCL with a free software license. Flash……
When you sit down to write a recommendations system, there are quite a few well-practiced techniques you can use, and it’s difficult to know in advance how well they are going to work out when applied to your data. Thanks to the Netflix prize, which was initiated in 2006……
