In our tutorials, we present you a portion of unique industrial practical experience on efficient data labeling via crowdsourcing shared by both leading researchers and engineers from Yandex. Majority of ML projects require training data, and often this data can only be obtained by human labelling. Moreover, the more applications of AI appear, the more nontrivial tasks for collecting human labelled data arise. Production of such data in a large-scale requires construction of a technological pipeline, what includes solving issues related to quality control and smart distribution of tasks between workers.
We invite beginners, advanced specialists, and researchers to learn how to collect labelled data with good quality and do it efficiently.