Combining Human Knowledge with Machine Learning for Robust Data Flows

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 many times humans are better at labeling content than machines. However, when we combine human knowledge with machine learning, we can create truly robust data flows. With that being said, what’s the best way to go about it? Solution #1: Active Learning Activ Learning, also known as semi-supervised machine learning,…


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