Probabilistic programming is powerful addition to your AI/ML tool belt.
In particular it can be useful in low data situations (and you never have enough data), to take advantage of hard learned domain knowledge and to reason under uncertainty.
Today there are many tools and frameworks to help you build probabilistic models and our focus is on coming together to explore, learn, and teach how to use them.
We do often have presentations and lighting talks and the main goal is to foster discussion and exchange of ideas and knowledge so everyone is expected to contribute at each meeting.
Topics for the meetings include tutorials (Stan, MyMC, Pyro, Edward, Venture, Anglican, Church, Figaro, etc), Algorithms (MCMC, ADVI, etc), modeling process and techniques, domain applications, and cutting edge research (Bayesian Neural Nets).
Everyone interested in machine learning and probabilistic methods with any background, experience or demographic is welcomed to attend and participate.
To reiterate that this is a 'study group' style meetup focused on discussions and collaboration and not presentations as much. All experience levels are welcome. The more you put into it the more you'll get out of it so do what you can to read the materials and come prepared to share your thoughts and help others.
Also, I don't provide food at the meetings (though you are welcome to bring your own) so please plan accordingly. If that is an issue, let me know and we can discuss what we can do in the future.