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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
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode