Bayesian Methods for Hackers is the source repository for Bayesian Methods for Hackers, an educational book about Bayesian inference and probabilistic programming. It is written from a computation-first perspective, prioritizing intuition, examples, and executable notebooks over heavy mathematical formalism. The project introduces readers to uncertainty, Bayesian modeling, MCMC, priors, posteriors, and real-world probabilistic reasoning. It includes notebook-based chapters that let learners run and modify examples directly. The material is especially useful for programmers, data scientists, and technically curious readers who want to learn Bayesian methods through code. It remains a widely referenced entry point for making Bayesian statistics feel practical and approachable.
Features
- Notebook-based Bayesian lessons
- Computation-first explanations
- Probabilistic programming examples
- MCMC learning material
- Real-world modeling exercises
- Open educational book format