Probabilistic Programming

Past Presentations

Probabilistic Programming from Scratch

This talk is for anyone who deals with real world data. Such data is always incomplete or imperfect in some way. Bayesian inference is a framework that allows us to draw conclusion from that data. And despite a reputation for mathematical and computational complexity, you don’t need a...

Mike Lee Williams Research engineer @Cloudera Fast Forward Labs
Software Is Eating the World, ML Is Going to Eat Software

"Democratizing ML" is a hot topic these days - particularly in industry. Efficiency, composability and accessibility of machine learning technology are active areas of investment for many research and product groups. Unfortunately, while machine learning has the potential to fundamentally improve...

Joe Pamer Language Designer Working on ML + Tooling @Facebook & previously Developed TypeScript, F#, & Swift

Interviews

Mike Lee Williams Research engineer @Cloudera Fast Forward Labs

Probabilistic Programming from Scratch

What do you want someone to leave your talk with? 

The audience will leave with a strong non-mathematical intuition for how Bayesian inference allows us to quantify the strength of conclusions drawn from real-world data. They’ll hopefully be excited to solve other toy problems with the tool we put together during the talk, and keen to check out PyMC3.

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