Shreya Shankar — Operationalizing Machine Learning
Gradient Dissent: Conversations on AI
Is There a Difference Between Structured and Unstructured Data?
We often see a separate MLOps team that's sort of doing the infrastructure while other people are kind of doing the training. We required that everyone was an ML engineer responsible for a model or like pinged when the model predictions are bad or someone's complaining at some point in their career. These ML engineers have so much on their backlog, like if they can kick off or retrain and get to something else on the backlog and it works 80% of the time, that is going to be the solution. That is the best solution. I feel like more ML researchers should know this, but we could be actually maybe unbiased.
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