The Conference for Machine Learning Innovation

Building Human-in-the-Loop Machine Learning Systems – Fashion 2.0

Session
Join the ML Revolution! Register until November 7th: ✓Save up to € 210 ✓ 10% Team Discount Register Now
Join the ML Revolution!
Until Conference starts:
✓Special discount for Freelancers
✓10% Team Discount
Register Now
Join the ML Revolution!
Until Conference starts:
✓Special discount for Freelancers
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
✓Save up to 500 €
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until March 5:
✓ML Intro Day for free
✓Save up to 500 €
✓10 % Team Discount
Register Now
Infos
Every day at Outfittery, hundreds of stylists use personalised styling systems to create personalised outfits for men all around Europe. They do so by talking to and understanding their customers’ needs, rather than a customer browsing an e-commerce catalogue.
These tools heavily rely on machine learning to perform things such as 
  • Personalisation: Will a customer like a particular type of clothing, will it fit them, do they identify with the brand?
  • Decision Support: Whats a good shirt to go with these shoes? Does this outfit make sense for the event the customer is about to attend? 
  • Logistics: Is this item in stock? Where in the world is it at the moment, will we have it in time to send it to the customer or should we replace it automatically?
  • Customer Support: Our stylists talk directly to the customers to understand their needs. Should we do something different based on the feedback they give us?
To make this possible, we have machine learning embedded everywhere to help our stylists make the right decisions and be more efficient. This requires unique data collection, tooling and innovation. In this talk, Steven will explain the various people, products, and system processes to bring this all together.

Behind the Tracks