Machine Learning textbook with a Bayesian Perceptive

We had a discussion on the pymc_devs channel about what books to recommend to people wants to learn Machine Learning from a Bayesian perspective. I think it is worth to share:

To me, the classic Christopher Bishop is a must read:

@colcarroll and @fonnesbeck recommended Murphy along with Hastie & Tibshirani:


Bayesian Data Analysis, by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin is another good read


The “puppy book” by John Kruschke is a good read, even for un-initiated. "Doing Bayesian Data Analysis"

Murhpy is my go-to reference for most of ML

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I read the first few chapters of ‘Statistical Rethinking’ by McElreath and really like his style of writing.

In general I find that reading several authors on the same subject is very helpful to develop understanding.

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Yes, this book is really great. @aloctavodia has ported much of it to PyMC3.

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