Is MLOps Leaving the Software Engineer Behind?

A few years ago, Venture beat reported that only 13% of data science projects make it into production. Companies hired data scientists but neglected to put proper supports in place to productionize their efforts. They siloed the data scientists from the rest of the organization, gave them some API keys, and asked them to weave gold. This failed terribly and, thus, in the mists of a deep learning revolution and new AI summer, the enterprise was left wondering how and why they couldn't get a piece of the pie. Through a combination of process and tooling, MLOps promises to make your data science teams efficient by enabling them to build, test, ship, and measure models faster.