Probabilistic Programming and Bayesian Methods for Hackers
An introduction to Bayesian inference and probabilistic programming using Python and PyMC, with a computational-first approach.
What is Probabilistic Programming and Bayesian Methods for Hackers?
Bayesian Methods for Hackers is an introductory book and educational resource that teaches Bayesian inference and probabilistic programming using Python and the PyMC library. It focuses on a practical, computational-first approach to understanding Bayesian methods, providing interactive examples and case studies to bridge the gap between theory and application.
Data scientists, machine learning practitioners, statisticians, and programmers who want to learn Bayesian methods without a heavy mathematical background, or who prefer a hands-on, code-driven approach to statistics.
It demystifies Bayesian inference by prioritizing computational understanding over complex mathematics, offering interactive Jupyter notebooks with real-world examples. It serves as a practical gateway to probabilistic programming, especially for those using Python's scientific stack.
Overview
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Use Cases
Best For
- Learning Bayesian inference through practical coding examples
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