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Article: AutoML: the Promise vs. Reality According to Practitioners
Aug. 29, 2022, 9 a.m. | Doris Xin
InfoQ - AI, ML & Data Engineering www.infoq.com
Automation to improve machine learning projects comes from a noble goal, but true end-to-end automation is not available yet. As a collection of tools, AutoML capabilities have proven value but need to be vetted more thoroughly. Findings from a qualitative study of AutoML users suggest the future of automation for ML and AI rests in the ability for us to realize the potential of AutoMLOps.
By Doris Xinai article artificial intelligence automated machine learning automl ml & data engineering neural networks reality
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