Guest
Piero shares the story of how Ludwig was created, as well as the ins and outs of how Ludwig works and the future of machine learning with no code. Piero is a Staff Research Scientist in the Hazy Research group at Stanford University. He is a former founding member of Uber AI, where he created Ludwig, worked on applied projects (COTA, Graph Learning for Uber Eats, Uber’s Dialogue System), and published research on NLP, Dialogue, Visualization, Graph Learning, Reinforcement Learning, and Computer Vision. Topics covered: 0:00 Sneak peek and intro 1:24 What is Ludwig, at a high level? 4:42 What is Ludwig doing under the hood? 7:11 No-code machine learning and data types 14:15 How Ludwig started 17:33 Model performance and underlying architecture 21:52 On Python in ML 24:44 Defaults and W&B integration 28:26 Perspective on NLP after 10 years in the field 31:49 Most underrated aspect of ML 33:30 Hardest part of deploying ML models in the real world Learn more about Ludwig:
