Braden Hancock, co-founder and head of technology and research at Snorkel AI, will discuss how Snorkel is used by Fortune 500 companies to break through a fundamental bottleneck in machine learning: manually labeling training data.
Since its inception at the Stanford AI lab in 2015, Snorkel has been used at some of the world's largest organizations across a variety of industries including finance, insurance, healthcare, and retail, and is now being taught in textbooks and ML curricula at some of the world's best universities.
In this webinar, you'll learn how Snorkel's programmatic approach to data labeling works, with concrete examples and intuitive explanations of the key concepts.
We will cover
- What is the Snorkel approach to ML and how does it work
- The four primary steps in the iterative AI application development loop powered by Snorkel
- The role each part in a Snorkel pipeline plays, from labeling functions to label models and advanced analysis tools that utilize label provenance
- How banks, healthcare providers, insurers, and government agencies have accelerated their AI applications development with Snorkel Flow, a platform built by Snorkel AI team.
Co-founder and Head of Technology
About the presenter
Braden is a co-founder and Head of Technology at Snorkel AI. Before Snorkel, Braden researched and developed new interfaces to machine learning systems in academia (Stanford, MIT, Johns Hopkins, BYU) and industry (Facebook, Google).