[CS 520](https://web.stanford.edu/class/cs520/) * [Introduction](https://web.stanford.edu/class/cs520/abstracts/re.html) * [Slides](https://web.stanford.edu/class/cs520/abstracts/re.pdf) * [Video](https://youtu.be/ZWM-Dlw3VCM?t=2100) Paper * [[1605.07723] Data Programming: Creating Large Training Sets, Quickly](https://arxiv.org/abs/1605.07723) * [Snorkel: rapid training data creation with weak supervision | SpringerLink](https://link.springer.com/article/10.1007/s00778-019-00552-1) * [Snorkel AI: Programmatic Approach to Labeling Training Data | by Yitaek Hwang | Towards Data Science](https://towardsdatascience.com/snorkel-ai-programmatic-approach-to-labeling-training-data-11973cf14f70) * [snorkel-team/snorkel: A system for quickly generating training data with weak supervision](https://github.com/snorkel-team/snorkel) * [snorkel-team/snorkel-tutorials: A collection of tutorials for Snorkel](https://github.com/snorkel-team/snorkel-tutorials) * [**Get Started · Snorkel**](https://www.snorkel.org/get-started/) * [[1812.00417] Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale](https://arxiv.org/abs/1812.00417) * [[1909.05372] Overton: A Data System for Monitoring and Improving Machine-Learned Products](https://arxiv.org/abs/1909.05372) * [p33-re-cidr20.pdf](http://cidrdb.org/cidr2020/papers/p33-re-cidr20.pdf) Article * [Weak Supervision for Science and Medicine: A Year in Review](https://hazyresearch.stanford.edu/ws4science)
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