Think Bayes
by Allen B. Downey · first published 2013
82% recommend18% neutral
Why HN recommends it
Programmer-friendly introduction to Bayesian statistics that builds ideas up in Python code rather than heavy math; free, accessible, and a good first step before PyMC or machine learning books.
Summarised by Claude from recommending comments
<h2>Printing History</h2> <dl> <dt>September, 2013:</dt><dd>First Edition</dd> <dt>2013-09-10:</dt><dd>First release</dd> <dt>2014-02-10:</dt><dd>Second release</dd> <dt>2014-08-22:</dt><dd>Third release</dd> <dt>2016-06-03:</dt><dd>Fourth release</dd> </dl>
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The author Alan B. Downey has released quite a few free books: Check out http://www.greenteapress.com/ including: Think Python : http://www.greenteapress.com/thinkpython/thinkpython.html Think Bayes : http://www.greenteapress.com/thinkbayes/index.html Think Complexity : http://www.greenteapress.com/complexity/index.html Think Stats : http://www.greenteapress.com/thinkstats/index.html
on “The Little Book of Semaphores” ↗…language) 3. Internet Core Protocols: The Definitive Guide - Hall (not a work of any particular genius, but this is stuff everyone should know, in my opinion) 4. Applied Cryptography - Schneier 5. Think Bayes - Downey 6. Interconnections: Bridges, Routers, Switches and Internetworking Protocols - Perlman
on “Code Interview Reading List” ↗…glad to see I'm not the only one. I don't have any recommendations for linear algebra, but for stats and probability (which I always found intimidating in the past), Allen Downey's "Think Stats" and "Think Bayes" did the trick.
on “A Software Engineer’s Adventures in Learning Mathematics” ↗…(Bishop): http://www.amazon.com/Pattern-Recognition-Learning-Informati... There are some great resources/books for Bayesian statistics and graphical models. I've listed them in (approximate) order of increasing difficulty/mathematical complexity: Think Bayes (Downey): http://www.amazon.com/Think-Bayes-Allen-B-Downey/dp/14493707... Bayesian Methods for Hackers (Davidson-Pilon et al): https://github.com/CamDavidsonPilon/Probabilistic-Programmin... Doing Bayesian…
on “Ask HN: What are some good Machine Learning resources?” ↗How does it compare/contrast with: - Wasserman's All of Statistics? (which I haven't read/worked on) - Downey's Think Stats and Think Bayes? (which I've read in bits and pieces and have found amazing) - Any other well known Stats or Probability text?
on “Stats without Tears (2016)” ↗A good (free) explanation of Bayesian Stats using Python: Downey's Think Bayes http://www.greenteapress.com/thinkbayes/
on “Bayesian updating of Probability Distributions” ↗My favorite explanation of this (posed instead as the Locomotive problem) is in Allen Downey's "Think Bayes," pp.22 It's online too, and worth reading! http://www.greenteapress.com/thinkbayes/
on “German tank problem” ↗I'm still learning about Bayesian Stats myself, but so far I've really enjoyed Think Bayes[0] by Allen Downey. He's a great writer and one of his other books was recently on the front page here. 0 - http://www.greenteapress.com/thinkbayes/
on “Ask HN: Bayesian Statistics – where do I start?” ↗…work. Here are a few other books I found to be enjoyable and well-written: Programming Erlang by Joe Armstrong Programming Elixir by Dave Thomas Seven (more) Languages In Seven Weeks by Bruce Tate Think Bayes, Think OS, How To Think Like A Functional Programmer (Think OCaml) and The Little Book of Semaphores by Allen B. Downey
on “Ask HN: What are some of the best written programming books?” ↗Speaking of Bayes, there's a great book by Allen B. Downey 'Think Bayes' http://www.greenteapress.com/thinkbayes/ available as free PDF or (if you wish to support the author, which I did) a paperback from Amazon. It teaches Bayes theorem accompanied with Python code examples,…
on “Bayes’ Theorem – What is it and what is it good for?” ↗A relevant book is Think Bayes [1] by Allen B. Downey. It also uses only pure Python to solve simple problems of Bayesian inference. I like the simplicity of the way it communicates the ideas of Bayesian approach. But the subject…
on “Probabilistic programming from scratch” ↗This is the "online" (abridged) version of this book: https://www.amazon.com/Bayesian-Methods-Hackers-Probabilisti... There's a full version of another good book ("Think Bayes: Bayesian Statistics in Python") available as a PDF from the publisher here: http://greenteapress.com/wp/think-bayes/ (related Amazon reviews) https://www.amazon.com/Think-Bayes-Bayesian-Statistics-Pytho...
on “Probabilistic Programming and Bayesian Methods for Hackers (2013)” ↗I recommend Think Bayes by Allen Downey if you want to study more. It's a free book available online. http://www.greenteapress.com/thinkbayes/thinkbayes.pdf
on “The German Tank Problem” ↗It has been a few years since I looked at this, and it looks like a lot has been added since then. It's certainly worth a look. But at the time I found Allen B. Downey's "Think Bayes" to be a more thorough and comprehensive resource: https://greenteapress.com/wp/think-bayes/
on “Probabilistic Programming and Bayesian Methods for Hackers (2013)” ↗…title should reflect that this is a newly released version (previous was 2019)? Like many, I found Richard's lectures to be fantastic to get better intuition about the underlying processes. This course + Think Bayes[0] by Allen Downey did more for my statistical literacy than multiple college + graduate courses. [0] https://allendowney.github.io/ThinkBayes2/index.html#
on “Statistical Rethinking [video]” ↗