gdpr

Similar experience over here. (G)ARCH models are severely underserved in Python, and I could not be bothered to learn a Probabilistic programming abstraction like Pyro or Stan just to build a quick prototype myself.

Chose Julia instead. Took 4 hours to get everything sorted out (including getting IT to allow Julias package manager to actually download stuff) and have the first model running just putting a paper into code. Since code is just writing the math, this is a vast communication improvement.

After fiddling around withit at home for a week, this was the first professional experience and I'm blown away.

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... [1] http://www.inference.org.uk/mackay/itila/book.html