NAVER LABS Europe seminars are open to the public. This seminar is virtual and requires registration
Date: 19th May 2022, 4:00 pm (GMT +2:00)
Cleanlab 2.0: Making ML work with messy, real-world data
Abstract: I’ll start the talk with an overview of Cleanlab 2.0, an open-source framework that lets you find label and quality issues in any classification dataset, often in one line of code. Next, I’ll share an overview of confident learning, the underlying field of theory and algorithms that make Cleanlab work under the hood.
I’ll finish the talk with concrete real-world use cases of Cleanlab, namely (1) how companies like Amazon, Google, Tesla, and Wells Fargo used Cleanlab technology and (2) how to automatically find and fix issues in your own dataset in a step-by-step working tutorial. I’ll leave time at the end and questions pertaining to both the underlying theory and the applications at Cleanlab are welcome.
About the speaker: Curtis Northcutt is a computer scientist and entrepreneur focusing on machine learning and AI that works reliably for and empowers people. He is the CEO and co-founder of Cleanlab, an open-source company that automatically finds and fixes label issues in any dataset and makes AI solutions work for real-world, messy data. Curtis completed his PhD in Computer Science at MIT and is the recipient of the MIT Thesis Award, the NSF Fellowship, and the Goldwater Scholarship. Prior to Cleanlab, Curtis worked at several leading AI research groups, including Google, Oculus, Amazon, Facebook, Microsoft, and NASA.