Evgeniya
Evgeniya is a Data Evangelist at Toloka: data labelling platform for machine learning pipelines, used world-wide by approximately 2,000 large and small businesses.
Her career path is made up of being an analyst-developer, an machine learning engineer, a solution architect and a business analyst, including 2 years experience of working with crowdsourcing. Evgeniya’s background is in Artificial Intelligence & Data Engineering, she’s currently doing her masters at Technical University of Munich.
Sessions
The talk includes the presentation of Crowd-Kit - an open-source computational quality control library - followed by its demonstration.
Crowdsourced annotations in most cases require post-processing due to their heterogeneous nature; raw data contains errors, is biased and non-trivial to combine. Crowd-Kit provides various methods like aggregation, uncertainty, and agreements, which could be used as helping tools in getting an interpretable result out of data labeled with the help of crowdsourcing.