Bayesian inference and probabilistic programming

The Effective Data Scientist

Interview with Alex Andorra

Interviewing Alex Andorra about bayesian inference, probabilistic programming, and more was a pleasure.
Alex is a data scientist and modeler at the PyMC Labs consultancy. He's also an open-source enthusiast and core contributor to the python packages PyMC and ArviZ. Alex is also a contributor and instructor in the "Intuitive Bayes Introductory Course". This self-paced course is designed for data scientists and developers, where you'll learn Bayesian modeling with code, not math.
Alex also runs the amazing "Learning Bayesian Statistics" podcast!
If you love Python and Bayesian inference, catch this episode.

How Alex began his path on statistical modeling and how he finds this a challenging, versatile, and creative

How Alex and his agency do with clients using multilevel regression and post-stratification and tracking opinion through time

How the community around PMYC is growing and contributing to development in an open source format

Alex hosts a podcast that covers a wide variety of topics, including political elections, healthcare, neuroscience, and the market

Alex's suggestions of what books to read and how to effectively contribute to open source projects, and stay active in the community

What are the benefits of joining online communities for learning

and more..

Listen to this episode now and share this with your friends and colleagues!