Piero Molino — The Secret Behind Building Successful Open Source Projects

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: https://ludwig-ai.github.io/ludwig-docs/ Piero's Twitter: https://twitter.com/w4nderlus7 Follow Piero on Linkedin: https://www.linkedin.com/in/pieromolino/?locale=en_US Get our podcast on these other platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/google-podcasts YouTube: http://wandb.me/youtube Soundcloud: http://wandb.me/soundcloud Tune in to our bi-weekly virtual salon and listen to industry leaders and researchers in machine learning share their research: http://wandb.me/salon Join our community of ML practitioners where we host AMA's, share interesting projects and meet other people working in Deep Learning: http://wandb.me/slack Our gallery features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, and industry leaders sharing best practices: https://wandb.ai/gallery