Changing assumptions and ever-changing data mean the work doesn’t end after deploying machine learning models to production. These best practices keep complex models reliable. Agile development teams ...
For anyone managing IT ops, setting performance thresholds has been a big, and tedious, part of the job. I mean, if you don’t tell the system that 8,000 server calls in an hour is way too many, how’s ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
At its very core, machine learning is an advanced means of making sense of massive amounts of data, and for this reason, machine learning and monitoring should go hand-in-hand. With the ability to ...
Once machine learning models make it to production, they still need updates and monitoring for drift. A team to manage ML operations makes good business sense As hard as it is for data scientists to ...
Citation: Ha NT, Manley-Harris M, Pham TD, Hawes I. A Comparative Assessment of Ensemble-Based Machine Learning and Maximum Likelihood Methods for Mapping Seagrass Using Sentinel-2 Imagery in Tauranga ...
Aliso Viego, California-based Sentrian's remote patient monitoring program has been in a pilot with COPD patients at Anthem subsidiary CareMore for about six months, Sentrian founder and Chief Medical ...
Manual audits machine learning improves drug diversion prevention by reducing errors, saving staff time, and enhancing patient safety in hospitals.
Hero Medical Technologies Awarded OTA by MTEC to Advance Machine Learning and Wearable Sensing for Field Triage ...
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