ML System Design: Federated Learning

NILG.AI, together with Neu.ro decided to try a format similar to a Reading Club, where the topic is not a specific paper but an entire research area. After a short discussion, we had a System Design part where the team described a specific use case to apply the new approach. Ideally, the discussion would stick to the format of a typical System Design interview — however, our first exploratory attempt appeared to be rather a freestyle.

In our Session #1, held on 2021–05–27, an ML team from NILG.AI led by Paulo Maia, and an MLOps team from Neu.ro led by Artem Yushkovsky met. The leaders researched the topic preliminarily and prepared a theoretical presentation for ~30-min so that everyone could be on the same page. Then, we had a ~90-minute practical part where both teams discussed technical aspects (both ML and MLOps) of the architecture for a given use-case, putting their thoughts to a Miro board.

The outcomes are shared in a Medium article (7-10 min read), where you can see a high-level overview of the outcomes of this session and the takeaways.

Let us know if you have any comments about this topic!

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