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4min chapter
Jordan Edwards: ML Engineering and DevOps on AzureML
Machine Learning Street Talk (MLST)
Machine Learning - The High Interest Credit Card of Technical Debt
Ray Kurzweil: I wanted to spend more time talking about what the m l engineer does, ecause i think this is the role that, if you look in a lot of industry at the moment, they don't have the notion of an m l engineer. The key problem with m lops is the miopia of the data scientists. It's where does the model go after it's bein created? He says az m l has this concept of a pipe line, and it's like a work flow. And he adds we're also trying to look and see how we can take that same process flow in logic, and bring it to the open source community so that
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