Operationalizing machine learning: An interview study
Organizations rely on machine learning engineers (MLEs) to operationalize ML, ie, deploy
and maintain ML pipelines in production. The process of operationalizing ML, or MLOps …
and maintain ML pipelines in production. The process of operationalizing ML, or MLOps …
How open source machine learning software shapes ai
M Langenkamp, DN Yue - Proceedings of the 2022 AAAI/ACM …, 2022 - dl.acm.org
If we want a future where AI serves a plurality of interests, then we should pay attention to
the factors that drive its success. While others have studied the importance of data …
the factors that drive its success. While others have studied the importance of data …
" We Have No Idea How Models will Behave in Production until Production": How Engineers Operationalize Machine Learning
Organizations rely on machine learning engineers (MLEs) to deploy models and maintain
ML pipelines in production. Due to models' extensive reliance on fresh data, the …
ML pipelines in production. Due to models' extensive reliance on fresh data, the …
Threads, Buckets, and Impact: A Framework for Tool Accelerated Machine Learning Courses
JA Niemirowski - 2023 - digitalcommons.latech.edu
Artificial intelligence and machine learning (ML) have exploded in use, accessibility, and
awareness in the past few years, particularly with the release of ChatGPT in late 2022 …
awareness in the past few years, particularly with the release of ChatGPT in late 2022 …
[引用][C] Implementation and Evaluation of a Predictive Maintenance Course Utilizing Machine Learning
JA Niemirowski, KC Cruse, D Hall - 2023 ASEE Annual Conference & Exposition, 2023