Also this year, at our 10 year anniversary edition of PyData Amsterdam, we’ll host open source sprints! ️ Our open source sprints this year will be 2 sessions in parallel, with leading open source contributors Fokko Driesprong and Rob Zinkov of the respective packages PyIceberg and PyMC.
talk-data.com
Speaker
Rob Zinkov
3
talks
machine learning engineer and data scientist
My work covers how to more efficiently specify and train deep generative models as well as how to more effectively discover a good statistical model for your data. Previously I was a research scientist at Indiana University where I was the lead developer of the Hakaru probabilistic programming language.
Bio from: PyData Amsterdam 2025
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Talks & appearances
3 activities · Newest first
We talked about:
Rob’s background Going from software engineering to Bayesian modeling Frequentist vs Bayesian modeling approach About integrals Probabilistic programming and samplers MCMC and Hakaru Language vs library Encoding dependencies and relationships into a model Stan, HMC (Hamiltonian Monte Carlo) , and NUTS Sources for learning about Bayesian modeling Reaching out to Rob
Links:
Book 1: https://bayesiancomputationbook.com/welcome.html Book/Course: https://xcelab.net/rm/statistical-rethinking/
Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html
Outline: The Bayesian framework; Probabilistic programming; Creating scientific software packages; PyMC.