Introduction: Interior design and home decoration involve a high amount of guesswork. In addition to the visual appearance of each individual item, the arrangement of these items in a room and how well they fit together are also highly important. These considerations combine to create the notoriously subjective concept of……
This week in Wayfair Data Science’s explainer series, we’re discussing object pose estimation, an important problem in robotics and augmented reality (AR) applications. In robotics, when given a 3D model of an object a mobile robot must be able to localize it in space in order to manipulate it. This……
Introduction If you are a Wayfair customer looking for some wall art to decorate your house, chances are you will land on our wall art SuperBrowse page (see image below or link here). This page shows a grid of 48 products, all of which are pieces of wall art. Those……
Wayfair has a strong emphasis on causal inference when evaluating the impact of business strategies. The assumptions of experimentation and regression are critical to know your models are capturing true effects and not confounding variables. In this video, Wayfair data scientist Dan VanLunen outlines some of these key assumptions along……
This week in Wayfair Data Science’s explainer series, Senior Machine Learning Engineer Tim Zhang lays out what you need to know about training image synthesis. Training image synthesis is a fairly young project for the Computer Vision team at Wayfair. We have explored a few different use cases that can……
In January 2019, Wayfair Data Science was thrilled to host our third immersion program for graduate students in quantitative fields. Our largest round yet, this program brought 25 PhD candidates from 12 different universities to spend a week with the data science team at Wayfair’s headquarters in Boston. Longer than……
In this installment, Archi Mitra (Senior Machine Learning Engineer on the Computer Vision team) lays out an intro to Human-in-the-loop systems, which are used in every Computer Vision project here at Wayfair. Our Visual Search, Object Detection, Room & Style algorithm leverages this system to annotate training data and validate……
This week, Zephy McKanna sets out to explain Multi-Armed bandits. Here at Wayfair, we are constantly testing new algorithms, product sort orders, marketing, and other messages using epsilon-first Multi-Armed Bandits – also known as A/B tests. We are also employing some more interesting MAB algorithms, like Thompson Sampling, to dynamically……
This week in Wayfair Data Science’s explainer series, Tim O’Connor discusses experimentation in the context of data science. Experiments are crucial to data science, helping to determine which version of a model is to use in future iterations of a system or generating new sources of data unavailable in a……
Welcome back to Wayfair Data Science’s Explainer Series! This week, Afshaan Mazagonwalla will be speaking about Bayesian Machine Learning Wayfair uses Bayesian and Reinforcement Learning based techniques for balancing the exploration – exploitation trade off between new and popular items in ranking products on the website and for recommending sales……
Find out about how Wayfair tackles product recommendations in our first installment! Wayfair Data Science is composed of a number of sub-teams, each tackling a different set of specific business challenges. In order to give you a taste of the wide array of people and workstreams we have here……
