Read Lee Rehwinkel’s opinion on why “ML Ops” is the last mile of machine learning in this Tech Target article.
AI adoption is accelerating across industries, driven by a combination of concrete results, high expectations and a lot of money. Among the many new AI concepts and techniques launching almost daily, 10 AI tech trends in particular grab data scientists’ attention.
Machine learning operations (MLOps) isn’t a new concept, but it’s a relatively new “Ops” practice which operationalizes machine learning models. MLOps seeks to understand what works and doesn’t work in a model in order to create more reliable models in the future.
It’s the last mile of machine learning model building, and a practice that historically hasn’t been given much attention, said Lee Rehwinkel, VP of science at B2B pricing and sales software company Zilliant.
“It’s one of the reasons a lot of models never see the light of day, but it’s super important [because] you build a model but how do you know the uptime of that model? How fast is it going to make predictions? Does it need to be trained or retrained?” he said.