"Practical Crowdsourcing for Efficient ML" is an introduction to the practical aspects of running a crowdsourcing project. Students will design and run a full-cycle crowdsourcing project, from planning to getting results. We will look at how crowdsourcing can be used for complex business tasks that have repeated actions, such as moderating content or testing web services, in addition to data labeling for machine learning applications, such as:
- Computer vision
- Search relevance
- Speech recognition
- And much more 😊
The five-week "Practical Crowdsourcing for Efficient ML" course is useful for current and aspiring ML developers, data analysts, and researchers. The course is in English, does not require any special background, and is open to students anywhere in the world free of charge.