Practical Crowdsourcing for Efficient Machine Learning
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Course overview
- Provider
- Coursera
- Course type
- Free online course
- Level
- Beginner
- Deadline
- Flexible
- Duration
- 17 hours
- Certificate
- Paid Certificate Available
- Course author
- Oleg Pavlov
-
Understand the applicability, benefits and limits of the crowdsourcing approach
Integrate an on-demand workforce directly into your processes and build human-in-the-loop processes
Control the quality and accuracy of data labeling to develop high performing ML models
Design and run a full-cycle crowdsourcing project: from planning to getting labeled data
Description
This course will teach you efficient and scalable data labeling for ML and various business processes. The key here is the crowdsourcing approach, based on splitting complex challenges into small tasks and distributing them among a vast cloud of performers.You will get acquainted with crowdsourcing as a methodology, mastering certain steps and techniques that ensure quality and stable performance. All these techniques will be implemented in practice straight away: throughout the course, you’ll design your own crowdsourcing project.
