W-JAX | 4. - 8. November 2019, München

Decision Making based on Machine Learning at Outfittery

Dieser Talk stammt aus dem Archiv. zum AKTUELLEN Programm
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Dienstag, 7. November 2017
11:45 - 12:45

Outfittery’s mission is to provide relevant fashion to men. In the past it was our stylists that put together the best outfits for our customers. But since about a year ago we started to rely more on intelligent algorithms to augment our human experts. This transition to become a data driven company has left its marks on our IT landscape: In the beginning we just did simple A/B tests. Then we wanted to use more complex logic so we added a generic data enrichment layer.Later we also provided easy configurability to steer processes.And this in turn enabled us to orchestrate our machine learning algorithms as self contained Docker containers within a Kubernetes cluster. All in all it’s a nice setup that we are pretty happy with.  

It then really took us some time to realise that we actually had built a delivery platform to deliver just any pure function that our data scientists come up with – directly into our microservices landscape. We just now started to use it that way; we just put their R&D experiments directly into production… 🙂 

This talk will guide you through this journey, explain how this platform is built, and what we do with it.

Alle News der Java-Welt:
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