What we're about

What's happening London! We are firing up a local MLOps chapter for this amazing city.

The MLOps Community fills the need to share real-world Machine Learning Operations best practices from engineers in the field. While MLOps shares a lot of ground with DevOps, the differences are as big as the similarities. We needed a community laser-focused on solving the unique challenges we deal with every day building production ML pipelines.

We’re in this together. Come learn with us in a community open to everyone. Share knowledge. Ask questions. Get answers.

You can check out our Slack or our podcast that’s filled with tips and tricks to overcoming the common obstacles we’ve all hit in the real world. Find the solutions you need. Share, learn, and grow with us, as we work to bring standardization to the chaotic world of MLOps

Upcoming events (1)

Argo Workflows

Link visible for attendees

MLOps community meetup #106! On July 20, we will be talking to
Kemal Tugrul Yesilbek, Senior Machine Learning Engineer of Beat about Argo Workflows.

// Register at:

// Abstract:
One of the most popular, and useful, ways to productionize a machine learning solution is scheduled batch workflows. In this approach, we deliver predictions in regular intervals. There are many tools available allowing you to construct and schedule your workflows. When there are many options, it can be difficult to choose.

In this session, we will talk about how and why we switched from Kubeflow to Argo Workflows for batch workflows; how we approach employing a new MLOps tool; and why simplicity is the way to go forward.

// Bio:
Kemal is a Senior Machine Learning Engineer at Beat, one of the fastest-growing ride-hailing apps in Latin America. He studied software engineering and machine learning. He studied software engineering and machine learning. During his time in academia, he published machine learning solutions approaching human-level performance.

Kemal started his career as a data scientist. He founded Elify.io, a skill assessment tool for data-driven roles, which resulted in an exit. He is working as a machine learning engineer for the past years, delivering end-to-end machine learning-backed solutions.

// Final thoughts
Please feel free to drop some questions you may have beforehand into our slack channel (https://go.mlops.community/slack)
Watch some old meetups on our youtube channel:

Past events (101)

FLOps with Scaleout's Open-core Platform

This event has passed

Photos (114)