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MLOps Community

The MLOps Community is where machine learning practitioners come together to define and implement MLOps. Our global community is the default hub for MLOps practitioners to meet other MLOps industry professionals, share their real-world experience and challenges, learn skills and best practices, and collaborate on projects and employment opportunities. We are the world's largest community dedicated to addressing the unique technical and operational challenges of production machine learning systems.
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Event

time
5:00 PM - 6:00 PM, Dec 7 GMT
The Motivation for MLOps
As an emerging sub-discipline, MLOps still needs to prove itself inside many enterprises where ML may present significant opportunities. Focused on the needs of the ML and Enterprise Architect this talk discusses some of the key areas which motivate the a
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time
6:24 PM - 6:31 PM, Nov 25 GMT
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Content

Building Threat Detection Systems: An MLE's Perspective
video
There is a clear pattern that we have been seeing with some of these greats in MLOps. So many use writing as a forcing function to learn about where they have holes in their understanding of something. If you are not writing, this episode explains why writing is important for your own development. Jeremy goes into writing in depth as to how beneficial it is for him to write and for him to see that he doesn't understand something if he cannot re-articulate it in writing.
Dec 6th, 2022 | Views 23
The (Mostly) Art and Science of Designing an ML Feature
video
How do you design and build an ML feature from scratch with little ML knowledge and limited resource? How do you make sure your ML stays grounded in human needs? In this talk, we'll learn how Sewei, an indie maker, incorporates ML into her mobile app via a human-centered design process and everything else she's learned along the way.
Dec 1st, 2022 | Views 15
Driving ML Data Quality with Data Contracts
video
Andrew introduces the concept of Data Contracts and talks about how they at GoCardless are using it to improve the quality and reliability of data by empowering data consumers - including our Data Scientists - to work closely with the data generators and get the data they really need to power highly effective ML models and other data-driven products.
Nov 29th, 2022 | Views 94
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