[master_yoda_1]

Answer is not so black and white as everything in ml has to use probability. You can ignore this unless you are among 20 top researchers who are working on frontier of ml. Bayesian probabilistic techniques does not work or are very slow for any practical purpose.

[amkkma]

But does it aid in understanding regular models, as they might have a bayesian interpretation?

[master_yoda_1]

Yeh for sure, but it's an overkill. It's like reading quantum mechanics to understand Newtonian mechanics. If you want to get a feel of bayesian ml here is an easier book, "Regression and Other Stories" https://avehtari.github.io/ROS-Examples/

[amkkma]

Thanks. How's that relate to Gelman's BDA or statistical rethinking?

[master_yoda_1]

Bda is more advanced version of this book. Stats rethinking is also good and one can start from scratch as it has more code and less maths.

[dklend122]

Ty