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InfoQ Homepage Presentations Creating Robust Interpretable NLP Systems with Attention

Creating Robust Interpretable NLP Systems with Attention

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Summary

Alexander Wolf introduces Attention, an interpretable type of neural network layer that is loosely based on attention in human, explaining why and how it has been utilized to revolutionize NLP.

Bio

Alexander Wolf is a Data Scientist at Dataiku, working with clients around the world to organize their data infrastructures and deploy data-driven products into production. Prior to that, he worked on software and business development in the tech industry. He's passionate about the latest developments in Deep Learning/Tech and works at enriching Dataiku's NLP features.

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Recorded at:

Feb 24, 2019

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Community comments

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    by Jay Vercellone,

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    This dude just spoiled Westworld for me. Not cool.

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