
How to become a Bayesian (2016) - noch
https://alexanderetz.com/2016/02/07/understanding-bayes-how-to-become-a-bayesian-in-eight-easy-steps/
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gdpr
For anyone who wants to dig a bit deeper: PRML by Bishop [0]. An amazing work
as a general introduction to machine learning and Bayesian in general.
MacKay's book [1] is a bit more opinionated regarding Bayesian methods. Even
if you do not become purely Bayesian, it advances your understanding of to
approach data quiet a bit compared to the generic "oh data, lets throw a NN at
it".

[0] [https://www.microsoft.com/en-
us/research/people/cmbishop/prm...](https://www.microsoft.com/en-
us/research/people/cmbishop/prml-book/) [1]
[http://www.inference.org.uk/mackay/itila/book.html](http://www.inference.org.uk/mackay/itila/book.html)

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woodandsteel
About 40 years ago I was reading a business mathematics book and ran across a
section that, as I recall, started out with a basic probabilities equation and
derived the basic Bayesian equation in one step.

Am I remembering this right? If so could someone post it?

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hgoury
By definition: p(A|B) = p(A,B) / p(B) (1)

With the same definition, switching A and B roles, we have p(A, B) = p(B|A)
p(A) (2)

Plug (2) into (1) and you have Bayes rule.

~~~
woodandsteel
Thank you for the explanation.

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fingerlocks
I would really like to read the full paper for reason #3, but it’s paywalled.
The whole article feels like a big teaser with the real content locked away.

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chalst
The TL;DR of the article provides two links to the preprint, and in fact there
is a Springer version accessible without cost:
[https://link.springer.com/content/pdf/10.3758/s13423-017-131...](https://link.springer.com/content/pdf/10.3758/s13423-017-1317-5.pdf)

Even less friction than Sci-Hub is the Unpaywall browser extension
[http://unpaywall.org/products/extension](http://unpaywall.org/products/extension)
which finds links to unpaywalled content matching paywalled journal articles.

