Weekly roundup of MLOps and DataOps - Issue #8

Hello Hello,

This is the first newsletter in 2022. I wish you all a productive 2022. We can´t control our external world but we can control how we react to it. Today I start with Dr Seuss

David, Hamel, Marvin, Rimas, Zander aggregate and share their views on how to approach an MLOPS pipeline and have created a website with talks, examples and github repo with all the code

If you are into MLOPS and haven´t found a tool to handle the cadence anomaly, feature stores are your best bet. Here is link to the feature store summit

Chip has talked to ~30 companies in different industries about their challenges with real-time machine learning and outlines the solutions for (1) online prediction and (2) continual learning, with step-by-step use cases, considerations, and technologies required for each level.

If you have want a more structured deep dive into MLOPS Denmark University has created an interesting course with code .

And while on the subject of courses , don’t forget to checkout this awesome MLOPS course

Thats it for today, will see you guys in the next letter and keep pushing those ML models to production ;)

Subbu