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