Solving ML’s Biggest Problems with Human-In-The-Loop Machine Learning

by Angela Guess Lukas Biewald, CEO of CrowdFlower, recently wrote in Inside Big Data, “machine learning is getting easier because more and more of big players in the space are open-sourcing their algorithms. In the past year alone, IBM, Facebook, Google, and Microsoft have done so. Having those open-sourced algorithms means businesses spend far less time (and money) creating and fine-tuning their own models. Take all those things together and you can see why machine learning is near the peak of the technology hype cycle. There’s promise and ML is accessible. But there are two major issues that more and more companies are butting up against with regard to the promise of machine learning: accuracy and training data. And interestingly, both are solved with people. We call this human-in-the-loop machine learning.”…

Link to Full Article: Solving ML’s Biggest Problems with Human-In-The-Loop Machine Learning

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