On Tuesday, we hosted an online talk with the Stan Group discussing why probabilistic programming is generating so much excitement in the fields of machine learning and statistics. In essence, probabilistic programming is a powerful tool to help organizations make rational decisions under uncertainty.
Watching the recording, you will learn:
- What kinds of problems are a good fit for Bayesian inference
- How a model-centric approach changes data science workflows
- How to use probabilistic programming for revenue models
- What Hamiltonian Monte Carlo is and why it’s tricky to use
- What Stan is, what it does well, and what its limitations are
- What we’re excited about in the near future
This online talk part of a series of educational resources accompanying our recent research on probabilistic programming. Our research dives deeper into the topic, teaching readers how to build products using Bayesian inference models. To learn more or subscribe to our research, write to us at email@example.com.
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