Weekly roundup of MLOps and DataOps
By Subbu Banerjee
issues
Weekly roundup of MLOps and DataOps - Issue #8
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
Weekly roundup of MLOps and DataOps - Issue #7
We describe lessons learned from developing and deploying machine learning models at scale across the enterprise in a range of financial analytics applications. These lessons are presented in the form of antipatterns. Just as design patterns codify best softw…
Weekly roundup of MLOps and DataOps - Issue #6(MLOPS > ML)
If you have built your first model and are wondering how to move it to production using opensource tools, this free course is right for you
Weekly roundup of MLOps and DataOps - Issue #5
How many machine learning platforms run on Kubernetes? Which machine learning platforms can run in air-gapped environments? How common are feature stores in current machine learning platforms? Should you build or buy your MLPlatform, Ian hellstrom takes a det…
Weekly roundup of MLOps and DataOps - Issue #4
If you are a software engineer, the GOF design patterns book might/should be on your book shelf, following the same paradigm Valliappa Lakshmanan (Author), Sara Robinson (Author) and Michael Munn (Author) have come up design patterns for ML and MLOPS. And her…
Weekly roundup of MLOps and DataOps - Issue #3
Given the importance of MLOPS, Stanford has started the MLOPS course which is led by the awesome Chip Huyen. Do look at her blog posts which has quite some detail on MLOPS
Weekly roundup of MLOps and DataOps - Issue #2
Usenix OPML 2020 conference had a lot of good talks on ML in production, however the one that really caught my eye was the presentation by Daniel and Todd. If you want a quick read here is the summary
Weekly roundup of MLOps and DataOps - Issue #1
Welcome to the world of MLOps and DataOps - the secret sauce to move your machine learning to production.Every week, I will bring to you articles, opensource repositories, blog posts, conference highlights in ML and DataOps space. If you are trying to move ma…