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Weekly roundup of MLOps and DataOps - Issue #3

Weekly roundup of MLOps and DataOps
Weekly roundup of MLOps and DataOps - Issue #3
By Subbu Banerjee • Issue #3 • View online
Hello folks,
Welcome to the third issue. We have really interesting hand curated list which I read and found useful to send it across to my subscribers. Do enjoy…

Stanford Machine Learning System design course
The awesome Chip Huyenś course on ML systems. Chip has been advocating the use of MLOPS for quite some time and is a leading voice on MLOPS
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
CS 329S | Home
Software Engineering best practices applied to MLOPS
Software engineering has a headstart on productionizing software and its high time ML uses the best practices from software world
Its (already) time that Machine learning world borrows the hard earned principles from software engineering to not reinvent the wheel
How does one monitor ML in production
Alajendro shares his experiences with a well written blog post
Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance | by Alejandro Saucedo | Dec, 2020 | Towards Data Science
AWS shares the best practices around MLOPS
AWS has created an ML lens to their whitepaper series which details the MLOPS best practices in the AWS world
AWS mlops whitepaper
Finally a note of thanks to our sponsors
AbundanceAI is your go to stop for deploying ML in production with least hassle. They have successfully deployed ML in production in fortune 500 companies and will be happy to guide you in this process.
Did you enjoy this issue?
Subbu Banerjee

Weekly roundup of MLOps and DataOps

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