(books)= # Books :::::{container} full-width ::::{grid} 1 2 2 3 :gutter: 3 :::{grid-item-card} Bayesian Modeling and Computation in Python :img-top: https://bayesiancomputationbook.com/_images/Cover.jpg By Osvaldo Martin, Ravin Kumar and Junpeng Lao Hands on approach with PyMC and ArviZ focusing on the practice of applied statistics. [Website + code](https://bayesiancomputationbook.com/welcome.html) ::: :::{grid-item-card} Bayesian Methods for Hackers :img-top: https://camo.githubusercontent.com/4a0aca82ca82efab71747d00db30f3a68de98e82/687474703a2f2f692e696d6775722e636f6d2f36444b596250622e706e673f31 By Cameron Davidson-Pilon The "hacker" in the title means learn-as-you-code. This hands-on introduction teaches intuitive definitions of the Bayesian approach to statistics, worklflow and decision-making by applying them using PyMC. [Github repo](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) [Project homepage](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) ::: :::{grid-item-card} Bayesian Analysis with Python :img-top: https://aloctavodia.github.io/img/BAP.jpg By Osvaldo Martin A great introductory book written by a maintainer of PyMC. It provides a hands-on introduction to the main concepts of Bayesian statistics using synthetic and real data sets. Mastering the concepts in this book is a great foundation to pursue more advanced knowledge. [Book website](https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition) [Code and errata in PyMC 3.x](https://github.com/aloctavodia/BAP) ::: :::{grid-item-card} Doing Bayesian Data Analysis :img-top: https://jkkweb.sitehost.iu.edu/DoingBayesianDataAnalysis/DBDA2Ecover.png By John K. Kruschke Principled introduction to Bayesian data analysis, with practical exercises. The book's original examples are coded in R, but notebooks with a PyMC port of the code are available through the links below. [Book website](https://sites.google.com/site/doingbayesiandataanalysis/home) [PyMC port of the second edition's code](https://github.com/cluhmann/DBDA-python) ::: :::{grid-item-card} Statistical Rethinking :img-top: http://xcelab.net/rm/wp-content/uploads/2012/01/9781482253443-191x300.jpg By Richard McElreath A Bayesian Course with Examples in R and Stan. [Book website](http://xcelab.net/rm/statistical-rethinking/) [PyMC 3.x port of the code](https://github.com/pymc-devs/resources/tree/master/Rethinking) ::: :::{grid-item-card} Bayesian Cognitive Modeling: A Practical Course :img-top: https://images-na.ssl-images-amazon.com/images/I/51K33XI2I8L._SX330_BO1,204,203,200_.jpg By Michael Lee and Eric-Jan Wagenmakers Focused on using Bayesian statistics in cognitive modeling. [Book website](https://bayesmodels.com/) [PyMC 3.x implementations](https://github.com/pymc-devs/resources/tree/master/BCM) ::: :::{grid-item-card} Bayesian Data Analysis :img-top: https://www.stat.columbia.edu/~gelman/book/bda_cover.png By Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin A comprehensive, standard, and wonderful textbook on Bayesian methods. [Book website](https://www.stat.columbia.edu/~gelman/book/) [Examples and exercises implemented in PyMC 3.x](https://github.com/pymc-devs/resources/tree/master/BDA3) :::: :::::