MLOps vs. DevOps: What is the Difference?
Machine learning is a term almost everyone in the IT space has heard by now—but it’s not just a buzzword used in flashy presentations anymore. As machine learning has started to become more applied and less theoretical, the industry has begun to incorporate it into important projects.
We’re past the point of proving its value. The concern now is how to properly implement a successful machine learning project and confidently push it to production.
Machine learning is a term almost everyone in the IT space has heard by now—but it’s not just a buzzword used in flashy presentations anymore. As machine learning has started to become more applied and less theoretical, the industry has begun to incorporate it into important projects.
We’re past the point of proving its value. The concern now is how to properly implement a successful machine learning project and confidently push it to production.
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