In this episode, we explore how Shopify evolved its product classification system across three major stages: from a traditional logistic regression model with TF-IDF features, to a multi-modal approach combining text and images, and finally to Vision Language Models built on top of a standardized and evolving product taxonomy. We also look at how architectural design and inference optimization are just as important as model accuracy in real-world machine learning systems.
For more details, you can refer to their published tech blog, linked here for your reference: https://shopify.engineering/evolution-product-classification
