Webinar: How to set up an ML data labeling pipeline: best practices and examples

To access this webinar, please register here: https://hubs.li/Q0110TqT0

Topic: How to set up an ML data labeling pipeline: best practices and examples

Speaker: Magdalena Konkiewicz, Data Evangelist at Toloka

Magdalena holds a Master's degree in Artificial Intelligence from Edinburgh University. She’s worked as an NLP Engineer, Developer, and Data Scientist for businesses in Europe and America. She now teaches and mentors Data Scientists, and regularly contributes to publications like Towards Data Science.

Abstract:
Supervised Machine Learning projects typically require labeled data to train the algorithms. You want to use high-quality data that corresponds to the problem you are trying to solve. But how do you obtain this kind of data?

In this session, Magda will show you how to build data labeling pipelines through crowdsourcing. Crowdsourcing is a scalable approach that can be applied to a variety of domains. Magda will share some examples of real-life labeling projects and show you what best practices to apply in the process.

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