Even if you're working with 100% machine-created data, more than likely you're performing some amount of manual inspection on your data at different points in the data analysis process, and the output of your machine learning models.
Many companies including Google, GoDaddy, Yahoo! and LinkedIn use what's known as HITL, or Human-In-The-Loop, to improve the accuracy of everything from maps, matching business listings, ranking top search results and referring relevant job postings.
Why are we still at this point? Because the promise of fully-automated end-to-end flows is a false one. So if we have to have a human involved at some point, what’s the best way to go about it?
Join me for a complimentary webinar on Thursday April 14th at 7PM EST where I'll show you multiple ways to implement and leverage HITL processes as part of your data pipelines.