Your video guide to crowdsourcing from A to Z
AI-based products and services rely on large amounts of high-quality labeled data for training, tuning, and evaluating machine learning algorithms. We strongly believe that machine learning workflows will focus increasingly on data production.
The crowdsourcing approach is an effective way to collect and label large datasets with faster turnaround and lower costs compared to using a limited group of experts for data collection and annotation. Our 10 years of industry experience and research show that advanced crowdsourcing techniques can make all the difference in building top-quality datasets.
We created this series of video tutorials to get you acquainted with crowdsourcing – through theory and real-life case studies. This is the perfect opportunity to explore crowdsourcing techniques and apply your knowledge right away.
Choose from 3 tracks: ML and AI, Business and Marketing, or Social Sciences. Whatever your background, you can count on our tutorials to walk you through the basics.
Learn how to get a high-quality dataset and use it to train your neural model. This track is perfect if you or your colleagues are involved in ML/AI.