Wayfair DS Explains It All: Cole Zuber on Evaluating Recommender Systems

June 10, 2019

Serving effective personalized product recommendations is critical to providing a pleasant shopping experience for customers at Wayfair. To do this, t...

Wayfair DS Explains It All: Trent Woodbury on Handling Imbalanced Data

May 28, 2019

Most machine learning algorithms are designed to train on balanced datasets. Resultantly, when our data are highly imbalanced, a typical model will ha...

Wayfair DS Explains It All: Peter B. Golbus on Theoretical Machine Learning

May 13, 2019

This week in Wayfair Data Science’s Explainer Series, Data Science Tech Lead Peter B. Golbus discusses machine learning from a theoretical computer ...

Wayfair DS Explains It All: Esra Cansizoglu on Object Pose Estimation

April 29, 2019

This week in Wayfair Data Science’s explainer series, we’re discussing object pose estimation, an important problem in robotics and augmented real...

Wayfair DS Explains It All: Foundational Assumptions of Experimentation and Linear Regression

April 8, 2019

Wayfair has a strong emphasis on causal inference when evaluating the impact of business strategies. The assumptions of experimentation and regression...

Wayfair DS Explains It All: Tim Zhang on Training Image Synthesis

March 18, 2019

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...

Wayfair DS Explains It All: Tim O’Connor on Experimentation

February 4, 2019

This week in Wayfair Data Science’s explainer series, Tim O’Connor discusses experimentation in the context of data science. Experiments are cruci...

Wayfair DS Explains It All: Afshaan Mazagonwalla on Bayesian Machine Learning

January 21, 2019

Welcome back to Wayfair Data Science's Explainer Series! This week, Afshaan Mazagonwalla will be speaking about Bayesian Machine Learning Wayfair u...