st-tech/zozo-shift15m
SHIFT15M: Fashion-specific dataset for set-to-set matching with several distribution shifts
This project provides the SHIFT15M dataset, a specialized collection of fashion item images and related data for evaluating machine learning models. It helps data scientists and machine learning engineers working in e-commerce or fashion tech who need to test how well their recommendation or categorization systems perform when user preferences or item trends change over time. The dataset takes in fashion item images and associated metadata, and outputs labeled data splits tailored for various machine learning tasks like predicting item popularity or matching sets of outfits.
176 stars. No commits in the last 6 months.
Use this if you are developing machine learning models for fashion e-commerce and need a large, real-world dataset to test their robustness against shifts in data distribution, like changing fashion trends or user behavior.
Not ideal if you are looking for a dataset of general-purpose images or if your machine learning task is not related to fashion items or set-to-set matching.
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176
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Language
Python
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Last pushed
Oct 18, 2023
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