Introduction Every day, Wayfair receives tens of thousands of messages from customers, telling us about their experiences with our products and services through the likes of product reviews, return comments, and various surveys. Considering that our customers spend valuable time writing these, it is fair to assume that they have……
Most machine learning algorithms are designed to train on balanced datasets. Resultantly, when our data are highly imbalanced, a typical model will have atrocious recall. In this video, Wayfair Senior Data Scientist Trent Woodbury explains the three most common ways of handling this imbalanced data problem. Trent Woodbury……
This week in Wayfair Data Science’s Explainer Series, Data Science Tech Lead Peter B. Golbus discusses machine learning from a theoretical computer science perspective. In this video, we describe multiclass classification as an encoding task, i.e. a process for building compression schemes that convert large “files” (feature vectors) into small……
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……
An introduction by way of some marketing prose. Cutting edge intelligent systems. Big data at scale. World class ad tech to drive phenomenal growth in a multi-billion dollar business. Real-time tracking and personalization to engage millions of shoppers daily: Ad Tech & Customer Intelligence Engineering @ Wayfair. Meet the two…
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 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……
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……
So, you graduated college, spent half a decade in a quantitative PhD program, maybe took a postdoctoral fellowship….and now what? You may want to stay the course and pursue a tenure track faculty position at a university–or, you may not. While the pressure to remain within the academy post PhD……
Search is critical to the customer experience at Wayfair. What we show on the first page of results is incredibly important for users. The graph below shows what many people might already know when it comes to browsing and search habits: The majority of customers rarely look beyond the products…
