43 citations · 288 across the 47 of their papers we have counts for
3 papers · 1 filter
Operationalizing Machine Learning: An Interview Study
Shreya Shankar, Rolando Garcia, Joseph M. Hellerstein +1
Organizations rely on machine learning engineers (MLEs) to operationalize ML, i.e., deploy and maintain ML pipelines in production. The process of operationalizing ML, or MLOps, co…
Rethinking Streaming Machine Learning Evaluation
Shreya Shankar, Bernease Herman, Aditya G. Parameswaran
While most work on evaluating machine learning (ML) models focuses on computing accuracy on batches of data, tracking accuracy alone in a streaming setting (i.e., unbounded, timest…
The Sky Above The Clouds
Sarah Chasins, Alvin Cheung, Natacha Crooks +14
Technology ecosystems often undergo significant transformations as they mature. For example, telephony, the Internet, and PCs all started with a single provider, but in the United…