MLOps and DevOps: Why Data Makes It Different
O'Reilly on Data
OCTOBER 19, 2021
Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.
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