Bayesian methods take the spotlight in this episode with Alex Andorra, co-founder of PyMC Labs, and Jon Krohn. Learn how Bayesian techniques handle tough problems, make the most of prior knowledge, and work wonders with limited data. Alex and Jon break down essentials like PyMC, PyStan, and NumPyro libraries, show how to boost model efficiency with PyTensor, and talk about using ArviZ for top-notch diagnostics and visualizations. Plus, get into advanced modeling with Gaussian Processes. This episode is brought to you by Crawlbase, the ultimate data crawling platform. Interested in sponsoring a SuperDataScience Podcast episode? Email [email protected] for sponsorship information. In this episode you will learn: • Practical introduction to Bayesian statistics [04:54] • Definition and significance of epistemology [17:52] • Explanation of PyMC and Monte Carlo methods [27:57] • How to get started with Bayesian modeling and PyMC [34:26] • PyMC Labs and its consulting services [50:50] • ArviZ for post-modeling diagnostics and visualization [01:02:23] • Gaussian processes and their applications [01:09:02] Additional materials: www.superdatascience.com/793

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.

Transcript

Related