AWS Machine Learning Blog

JANUARY 5, 2024

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems.

Data Science 137

Data Science Data Drift DevOps Auto-complete 137

The MLOps Blog

MARCH 28, 2023

The DevOps and Automation Ops departments are under the infrastructure team. They also need to monitor and see changes in the data distribution ( data drift, concept drift , etc.) The infrastructure team focuses on technology and delivers tools that other teams will adapt and use to work on their main deliverables.

Machine Learning 59

Machine Learning Automation Data Scientist ML 59

The MLOps Blog

AUGUST 3, 2023

At a high level, we are trying to make machine learning initiatives more human capital efficient by enabling teams to more easily get to production and maintain their model pipelines, ETLs, or workflows. Jeff Magnusson has a pretty famous post about engineers shouldn’t write ETL. ML platform team can be for this DevOps team.

ML 52

ML Data Scientist Software Engineer Machine Learning 52