**Probabilistic Programming and Bayesian Methods for Hackers**

by Cameron Davidson-Pilon

**Publisher**: GitHub, Inc. 2013

**Description**:

This book is designed as an introduction to Bayesian inference from a computational understanding-first, and mathematics-second, point of view. The book assumes no prior knowledge of Bayesian inference nor probabilistic programming.

Download or read it online for free here:

**Read online**

(online html)

## Similar books

**Algorithmic Mathematics**

by

**Leonard Soicher, Franco Vivaldi**-

**Queen Mary University of London**

This text is a course in mathematical algorithms, intended for second year mathematics students. It introduces the algorithms for computing with integers, polynomials and vector spaces. The course requires no computing experience.

(

**14741**views)

**Mathematics in the Age of the Turing Machine**

by

**Thomas Hales**-

**arXiv**

Computers have rapidly become so pervasive in mathematics that future generations may look back to this day as a golden dawn. The article gives a survey of mathematical proofs that rely on computer calculations and formal proofs.

(

**10032**views)

**Think Stats: Probability and Statistics for Programmers**

by

**Allen B. Downey**-

**Green Tea Press**

Think Stats is an introduction to Probability and Statistics for Python programmers. This new book emphasizes simple techniques you can use to explore real data sets and answer interesting statistical questions. Basic skills in Python are assumed.

(

**12104**views)

**Mathematics for Algorithm and Systems Analysis**

by

**Edward A. Bender, S. Gill Williamson**-

**Dover Publications**

This text assists undergraduates in mastering the mathematical language to address problems in the field's many applications. It consists of 4 units: counting and listing, functions, decision trees and recursion, and basic concepts of graph theory.

(

**21946**views)