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Team Snorkel

The latest from Team Snorkel

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Applying Information Theory to ML With Fred Sala

In this episode of Science Talks, Frederic Sala – an assistant professor of Computer Science at the University of Wisconsin Madison and a research scientist at Snorkel discusses his path into machine learning, the central thesis that ties together his multidisciplinary research, his thoughts on the future of weak supervision, as well as his decision to go into academia.

May 19, 2021
Learn more about Applying Information Theory to ML With Fred Sala
Blog
Building Industrial-Strength NLP Applications With Ines Montani

In this episode of Science Talks, Explosion AI’s Ines Montani sat down with Snorkel AI’s Braden Hancock to discuss her path into machine learning, key design decisions behind the popular spaCy library for industrial-strength NLP, the importance of bringing together different stakeholders in the ML development process, and more.This episode is part of the #ScienceTalks video series hosted by the Snorkel AI team. You…

Apr 29, 2021
Learn more about Building Industrial-Strength NLP Applications With Ines Montani
Blog
Measuring NLP Progress With Sebastian Ruder

In this episode of Science Talks, Sebastian Ruder, Research Scientist at DeepMind, shares his thoughts on making AI practical with Snorkel AI’s Braden Hancock. This conversation covers progress made in the NLP domain with emerging research, new benchmarks like SuperGLUE, rich repositories and news sources that keep you in the loop and on top of what’s new in NLP, and more.

Mar 10, 2021
Learn more about Measuring NLP Progress With Sebastian Ruder
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Productionizing ML Research With Thomas Wolf

In this episode of ScienceTalks, Snorkel AI’s Braden Hancock Hugging Face’s Chief Science Officer, Thomas Wolf. Thomas shares his story about how he got into machine learning and discusses important design decisions behind the widely adopted Transformers library, as well as the challenges of bringing research projects into production. ScienceTalks is an interview series from Snorkel AI, highlighting some of the best work and ideas to make AI practical.

Feb 05, 2021
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Blog
Debugging AI Applications Pipeline

We’ll analyze major sources of errors during the four steps of building AI applications: data labeling, feature engineering, model training, and model evaluation.

Feb 03, 2021
Learn more about Debugging AI Applications Pipeline
Blog
Meet a Snorkeler at an Upcoming Event

We love meeting people in the data science and machine learning community. Here are a few upcoming events where you can meet Snorkelers.

Nov 17, 2020
Learn more about Meet a Snorkeler at an Upcoming Event
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