Fashion forecasting revolution:
a case study
Context & Scope
How to label data to evaluate new recognition models and release new client features.
Challenge of volume
Challenge of quality reliability
MyDataMachine’s team of 30 persons expertise in meticulously labelling & annotating fashion images.
Tagging over 1.5M images every month since 3 years.
Results for our client
20 M images delivered
10k deep learning models created
"Overall increase in volumes for data acquisition, which means we were able to add more data and increase our scope of modules. Increase in quality reliability, in terms of daily image tagging. The ability and flexibility to test different and ad hoc use cases.”