Speaker

Rob Zinkov

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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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Bayesian Modeling and Probabilistic Programming - Rob Zinkov

2024-01-22 · DataTalks.Club Listen

podcast_episode

AI/ML C#/.NET HTML Monte Carlo

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