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……
Me: Doug, what are you doing? Doug: Solving the problem of class struggle with one of Greg’s classifiers. Me: Karl Marx should call his office. What do you mean by that? Doug: Let me explain… Class struggle at Wayfair search used to manifest itself as searches for ‘red cups’ that returned……
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……
