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…
Workplace diversity is not just an ethical issue. Teams that overcome diversity issues (e.g., gender, race, ethnicity, experience) often achieve greater productivity than homogeneous teams. If you’re surrounded by people who are different from you, you will be constantly challenged to reexamine facts, think deeper, and explain better. In this……
Top left to right: Yumeng Ma (University of Michigan), Steven Yin (Columbia), Michael Spece, Carnegie Mellon University), Quinn Donahoe (University of Pittsburgh), Cristian Gavrus (UC Berkeley) Bottom left to right: Ai Xu (Harvard), Elyse Norton (NYU), Aybike Ulusan (Northeastern),Yuija Zhou (Boston University) It’s safe to say that Wayfair’s Data……
Come find us! Next week, Wayfair Data Science will be hitting the road. Data scientists and engineers from across our teams will be attending the SIGIR Conference on Research and Development in Information Retrieval in Ann Arbor, Michigan, as well as the International Conference on Machine Learning (ICML) in Stockholm, Sweden. Here……
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……
Wayfair has over nine million unique items in its catalog, and tens of thousands of new ones are added every day. These products come from 8,000 different suppliers who sometimes sell the exact same products — two completely unrelated suppliers could be buying the exact same area rug from a……
