Comment by melling | Hacker News Reader

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Comment by melling | Hacker News Reader

I just recently got interesting in this topic and have been trying to organize my learnings on Github:

https://github.com/melling/Probabilistic_Programming

Currently trying to learn RStan (and R)

Found interesting examples for the Kaggle Titanic competition:

https://wiekvoet.blogspot.com/2015/09/predicting-titanic-dea...

https://www.r-bloggers.com/2015/10/predicting-titanic-deaths...

Putting examples here:

https://github.com/melling/Probabilistic_Programming/tree/ma...

Anyway, if anyone else has stumbled upon any other blogs, books, etc, I could use other good resources.

I am currently going through Statistical Rethinking [0], by R. McElreath. So far it's been great, all the code example and practice problems help comprehension.

I've also heard good things about Probabilistic Programming and Bayesian methods [1] by Cam Davidson Pilon.

[0] https://xcelab.net/rm/

[1] https://camdavidsonpilon.github.io/Probabilistic-Programming...

Anyone wanting Python/PyMC3 versions of the Statistical Rethinking code should check out [2].

[2] https://github.com/pymc-devs/resources/tree/master/Rethinkin...

Gelman's (one of the authors behind Stan) Bayesian Data Analysis is considered to be one of the best resources on this subject, so I suggest giving that a read. It's not the easiest book to work through though.

Here's a course from another author behind Stan on YouTube, working through it myself so can't say how good it bad it is, I think it uses the book too.

https://www.youtube.com/playlist?list=PLBqnAso5Dy7O0IVoVn2b-...

I started [0], but I got sidetracked. If anyone else has used this let me know as well.

[0] https://arxiv.org/abs/1809.10756

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