INFOTEC: Practice of efficient data collection

Overview

In this tutorial, we present a portion of our unique industry experience in efficient data labeling via crowdsourcing, shared by both leading researchers and engineers from Toloka. Most ML projects require training data, and often this data can only be obtained through human labeling. As new applications of AI emerge, there is ever-growing demand for human-labeled data collected in nontrivial tasks. Large-scale data production requires a technological pipeline that can successfully manage quality control and smart distribution of tasks between performers.

We introduce you to data labeling via public crowdsourcing marketplaces and present the key techniques for efficiently collecting labeled data. This is followed by a practice session, where participants choose one real label collection task, experiment with selecting settings for the labeling process, and launch their own labeling project on Toloka, one of the world's largest crowdsourcing marketplaces. During the tutorial, all projects are run on the real Toloka crowd. Participants also receive feedback and practical advice on making their projects more efficient. We invite beginners, advanced specialists, and researchers to learn how to collect high-quality labeled data, and do so efficiently.

Topics

Speakers

Daria Baidakova

TolokaDirector of Educational Programs

Nikita Pavlichenko

TolokaResearch Scientist

Sergey Koshelev

TolokaCrowd Solutions Architect

Polina Smirnova

TolokaEducational Project Manager

Organizers

Aljona Johnson

TolokaEducational Project Manager

Carlos Josuè Lavandeira Portillo

INFOTECDeputy Director of Innovation & Knowledge

Schedule