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Using Bayesian active learning with Label Studio

Overview

Baal is a Bayesian active learning library used for research and industrial applications. It provides methods to estimate sampling from the posterior distribution in order to maximize the efficiency of labelling during active learning. Baal is a member of the Pytorch ecosystem.

Benefits

By using Bayesian active learning in your labeling setup, you will be able to label only the most informative examples. This will avoid labelling duplicates and easy examples. Active learning loops are available as a feature of Label Studio Enterprise.

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