For our annual ML competition, we challenged university students to predict how many days a carrier takes to deliver packages.
Under the new machine learning model, buyers are recommended items that are more aligned to their shopping interests on eBay.
A step-by-step guide on how to build a state-of-the-art recommender system in an industrial setting.
A formal and interdisciplinary theory of learning and intelligence that combines biology, neuroscience, computer science, engineering and various branches of mathematics to provide a unifying framework, direction and a broader horizon for neural network and machine learning research.
Participating universities will structure listing data to help solve a real-world ecommerce challenge.
This feature enables our sellers to create cleaner listings.
eBay introduces Best Match to personalize buyers’ search feeds.
In recent eBay Tech Blog articles, we presented the Unified AI platform called Krylov and our pythonic tool to interact with the platform, PyKrylov. In this article, we introduce our Natural Language Processing framework built on top of the AI platform.
We challenged more than 100 college students at seven universities to structure listing data using AI and machine learning.
Part of our mission within Core AI at eBay is to develop computer vision models that will power innovative and compelling customer experiences. But how can we compare several visual search models and say which of them works better? This article will describe a method that is tackling this problem directly from the eyes of the users.