Coffee Sessions #105

Cleanlab: Labeled Datasets that Correct Themselves Automatically

Pioneered at MIT by 3 Ph.D. Co-Founders, Cleanlab is an open-source/SaaS company building the premier data-centric AI tools workflows for (1) automatically correcting messy data and labels, (2) auto-tracking of dataset quality over time, (3) automatically finding classes to merge and delete, (4) auto ml for data tasks, (5) obtaining and ranking high-quality annotations, and (6) training ML models with messy data. Most of the prescriptive tasks (finding issues) can be done in one line of code with their open-source product: https://github.com/cleanlab/cleanlab.

In this episode

Curtis Northcutt

Curtis Northcutt

CEO & Co-Founder, Cleanlab

Curtis Northcutt is the CEO and Co-Founder of Cleanlab focused on making AI work reliably for people and their messy, real-world data by automatically fixing issues in any ML dataset. Curtis completed his Ph.D. in Computer Science at MIT, receiving the MIT Thesis Award, NSF Fellowship, and the Goldwater Scholarship. Prior to Cleanlab, Curtis worked at AI research groups including Google, Oculus, Amazon, Facebook, Microsoft, and NASA.

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Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.

Vishnu Rachakonda

Vishnu Rachakonda

Host

Vishnu Rachakonda is the operations lead for the MLOps Community and co-hosts the MLOps Coffee Sessions podcast. He is a machine learning engineer at Tesseract Health, a 4Catalyzer company focused on retinal imaging. In this role, he builds machine learning models for clinical workflow augmentation and diagnostics in on-device and cloud use cases. Since studying bioengineering at Penn, Vishnu has been actively working in the fields of computational biomedicine and MLOps. In his spare time, Vishnu enjoys suspending all logic to watch Indian action movies, playing chess, and writing.