Why You Should Switch to Interpretable Models for Accurate and Transparent Results 🔍
Discover how interpretable models can match the accuracy of black box models for both tabular and raw data, and learn why transparency matters in machine learning.
About this video
This lecture focuses mainly on the face that interpretable models can be created to be as accurate as black box models, both for tabular and raw data. The video has a focus on 2 techniques for interpretable neural networks: case-based reasoning and neural disentanglement.
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3.4K
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Duration
29:49
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Published
Mar 26, 2021
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