
Bayesian Machine Learning Explained - sndean
http://fastml.com/bayesian-machine-learning/
======
mastazi
This post has been sitting in my bookmarks for a while now - at first I liked
the initial part which is very clear and "beginner-friendly" \- the best bit,
however (and the main reason why I came back to the post a few times now), in
my opinion is the "Resources" section at the end, which is really exhaustive.

------
stared
For Bayesian I recommend PyMC3 (the default version of PyMC is still 2, but 3
is functional and in fast development). Once you know a bit of Bayesian
statistics, there is a wonderful tutorial in Jupyter Notebooks:
[https://github.com/markdregan/Bayesian-Modelling-in-
Python](https://github.com/markdregan/Bayesian-Modelling-in-Python)

(Also, I've learnt from it the practical difference of fixed priors vs
hierarchical priors.)

~~~
curiousgal
I get a 503 error on the actual notebook.

------
Dawny33
Nice post.

For getting started with Bayesian thinking and analytics, I highly recommend
"Doing Bayesian Data Analysis_ A Tutorial with R and BUGS" by John Krushke

~~~
jwr
Seconded. It is the only book I found with a practical, down to earth
approach. Highly recommended.

