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Monitoring Model Performance with Crowdsourcing

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Building a human in the loop system for ML observability - Magdalena Konkiewicz

About this event

In this hands-on workshop, we’ll go through all the stages of building a human-in-the-loop system that monitors the performance of a machine learning model.

We’ll cover:

  • Designing a system for monitoring model performance
  • Sampling the model’s predictions and using crowdsourcing for evaluating whether these predictions are correct
  • Visualizing the collected data
  • Automatically retraining the model when performance degrades
  • Using the collected data for retraining

By the end of this workshop, you’ll be able to design a similar system for monitoring the quality of your own ML models.

About the speaker:

Magdalena is a Data Evangelist at Toloka, a global data labeling company serving around 2,000 large and small businesses worldwide. 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.

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This event is sponsored by Toloka.ai.

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