A Practical Guide to Maintaining Machine Learning in Production

In the previous post, we discussed six little-known challenges after deploying machine learning. This follow-up will share some practices I've found useful to maintaining machine learning in production. With close to 20 suggestions, it can get overwhelming. Fret not, I'll highlight the top three must-haves and good-to-haves at the end of this post. We'll go through some practical tools to help with maintaining machine learning in prod. "Data is the New Oil." "Garbage in, Garbage Out." These clichés emphasize that clean input data is essential to your system.