This GitHub is maintained by Karan Goel and Laurel Orr from Hazy Research. Reach out to kgoel [at] cs [dot] stanford [dot] edu for questions, comments and feedback.
The following individuals and organizations have contributed to the development of this GitHub so far,
- Kabir Goel created the header artwork.
- Members of Hazy Research created the first version of this resource, including Michael Zhang, Mayee Chen, Maya Varma, Megan Lesczynski, Avanika Narayan, Dan Fu, Arjun Desai, Tri Dao, Khaled Saab, Sen Wu, Beidi Chen
- Piero Molino from Predibase added discussion around declarative machine learning
- Braden Hancock from Snorkel.ai contributed to weak supervision
- Jared Dunnmon from the Defense Innovation Unit edited multiple sections
- Alvin Ming and Sharon Li from U-Wisconsin contributed work in outlier detection
- Ce Zhang and Cedric Renggli from ETH-Zurich added discussion for data cleaning and MLOps
- Eugene Wu from Columbia added discussion for data cleaning
- Bo Li from UIUC added discussion around adversarial robustness
- Cody Coleman from Stanford added discussion for data selection
- Michael Hedderich from Saarland Informatics added discussion for data augmentation
- Dan Hendrycks from UC-Berkeley added discussion around data augmentation and robustness.
- Sabri Eyuboglu and James Zou from Stanford added discussion around data deletion, valuation and augmentation
- Ivan Zhou from Landing AI added a case study
- Huaizheng Zhang from NTU added discussion to MLOps
- Ying Sheng from Google added a case study for GMail
- Rolando Garcia from UC-Berkeley added discussion on model debugging
Thanks to everyone who has provided feedback on this resource, including Jacob Steinhardt at UC-Berkeley, James Zou, Matei Zaharia, Daniel Kang, Chelsea Finn from Stanford, Mike Cafarella from MIT, Ameet Talkwalkar from CMU.