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Asking Questions From Data Using Active Learning with Tivadar Danka
Asking Questions From Data Using Active Learning with Tivadar Danka
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Length:
28 minutes
Released:
May 21, 2018
Format:
Podcast episode
Description
One of the challenges of machine learning is obtaining large enough volumes of well labelled data. An approach to mitigate the effort required for labelling data sets is active learning, in which outliers are identified and labelled by domain experts. In this episode Tivadar Danka describes how he built modAL to bring active learning to bioinformatics. He is using it for doing human in the loop training of models to detect cell phenotypes with massive unlabelled datasets. He explains how the library works, how he designed it to be modular for a broad set of use cases, and how you can use it for training models of your own.
Released:
May 21, 2018
Format:
Podcast episode
Titles in the series (100)
Thomas Hatch by The Python Podcast.__init__