• Title: Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference Using Python and PyMC
• Author(s) Cameron Davidson-Pilon
• Publisher: Addison-Wesley Professional (October 12, 2015); eBook (Online Edition. Updated Continuously)
• License(s): MIT License
• Paperback: 256 pages
• eBook: Jupyter Notebooks
• Language: English
• ISBN-10/ASIN: 0133902838
• ISBN-13: 978-0133902839
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Book Description

Master Bayesian Inference through Practical Examples and Computation - Without Advanced Mathematical Analysis.

This book illuminates Bayesian inference through Probabilistic Programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention.

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.

• Cameron Davidson-Pilon has seen many fields of applied mathematics, from evolutionary dynamics of genes and diseases to stochastic modeling of financial prices.

• Amazon

• Bayesian Thinking
• Statistics, Mathematical Statistics
• Probability and Stochastic
• Python Programming
• Computational and Algorithmic Mathematics

• Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference
• The Mirror Site (1) - PDF
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