Best practices in training data collection and human-in-the-loop computing to make it possible to deploy imperfect machine learning algorithms for mission critical application. Lukas Biewald explains how you can make the best possible use of training data and why it is essential to making your machine learning work well.
Lukas Biewald is the founder and chief data scientist of CrowdFlower, a data enrichment platform that taps into an on-demand workforce to help companies collect training data and do human-in-the-loop machine learning. Previously, he led the Search Relevance team for Yahoo Japan and worked as a senior data scientist at Powerset. Lukas was recognized by Inc. magazine as a 30 under 30. Lukas holds a BS in mathematics and an MS in computer science from Stanford University. He is also an expert Go player.
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